Research Fellow jobs in Fremont, CA

Job DescriptionCLIENT HIGHLIGHTThe Client you will be working for is a Fortune 100 Oil and Gas Company. This opportunity will give you experience in the energy sector in the United States with a company that is a globally recognized leader in energy production and one of the biggest companies in the US.LOCATIONRichmond, CA 94801COMPENSATION$25-30 per hour SCHEDULEMonday- Friday // 40 hours per week On-site CONTRACT TERM1 year long contract with high likelihood of extension or conversion to full-time POSITION OVERVIEW – Research Technician I- This is an R&D laboratory technician position in the CCUS & Separations team in Build for Tomorrow unit under Molecular Conversion department. This position supports experimental research and development work in renewable and hydrocarbon fuels, working under the guidance and supervision of research engineers and chemists. The position is dynamic and requires a variety of laboratory skills depending on the project need. This is a safety sensitive position.RESPONSIBILITIES Assist in research and development of new physical and chemical separation processes for hydrocarbons at the lab, bench, and potentially pilot scale. Prepare separation agents (solvents, adsorbents, membranes) and evaluate them with various small-scale batch and flow units Operate, troubleshoot, and maintain separations test equipment (batch test reactors and pure compound microunits). Compile data and make basic calculations related to data workup. General upkeep of the laboratory, fabricating lab-scale pilot plants, performing routine instrument calibration, scheduling safety inspections, maintaining chemical inventory, purchasing equipment and chemicals, and filing data for interpretation by research engineers. Perform non-routine duties and tasks as required. Ensure attention to safety when working with chemicals, high-pressure, and high-temperature process units. Maintain a clean, neat, and safe laboratory according to safety policies and tenets. This includes keeping the lab up to date on safety inspections (e.g. regulator and relief valve inspections up to date). It also includes maintaining chemical inventory and other appropriate safety records for lab operations. Follow all safety regulations and procedures. May set up new small bench scale equipment as needed. Uses co-workers, the shops, and HES for more extensive building/modification of microunits. The job will occasionally require intense all-day sampling of experiment that is being run. Assists other Separations Laboratory technician as needed. Perform instrument calibration, preventive maintenance, troubleshooting, and repair on Gas Chromatographs, laboratory instruments, and other equipment. Fabricate, run, troubleshoot, and repair bench scale units as needed. Perform other duties as needed, such as packing & shipping samples, writing/updating procedures, data analysis, preparation of special reports, and ordering supplies. REQUIRED QUALIFICATIONS/SKILLS: College chemistry and strong mathematical skills. Experience working as a research assistant or in a laboratory environment Good computer and oral/written communication skills are important. This includes MS Outlook, Excel (data manipulation and graphing), and Word, along with analytical instrument software

Job DescriptionResearch Intern, Machine Learning Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. Our internships offer flexible commitment, with a minimum of 20 hours per week, ranging 12 to 24 weeks. We have various start dates available to accommodate your academic schedule. There may be opportunities for full-time employment upon successful completion of your PhD. You will contribute to the development of novel machine learning approaches for biological data analysis and interpretation You will design and implement experiments to evaluate and improve AI models using large-scale biological datasets You will collaborate with our interdisciplinary team to tackle complex challenges in molecular biology and drug discovery You will present your research findings and contribute to publications in top-tier conferences and journals You will have the opportunity to work on projects that directly impact the future of medicine and biotechnology Who We're Looking For You are currently pursuing a PhD in Machine Learning, Computer Science, Computational Biology, or a related field You have a strong background in deep learning, with experience in frameworks such as PyTorch or TensorFlow You have a proven track record of research, demonstrated by publications at conferences such as NeurIPS, ICML, ICLR, or relevant computational biology venues You are proficient in Python and have experience with large-scale data processing and analysis You have excellent problem-solving skills and the ability to work independently on complex research problems You are passionate about applying AI to solve real-world challenges in biology and medicine You have strong communication skills and can effectively present technical concepts to diverse audiences You thrive in a fast-paced, startup environment and are excited about making a significant impact in a growing field Bonus Points Experience with biological data analysis or computational biology projects Familiarity with generative AI models, such as transformers or diffusion models Contributions to open-source machine learning or bioinformatics projects Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of our patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. That's why we're committed to creating an engaging and enjoyable work environment. Our goal is to create a workplace that is fun, rewarding and fulfilling. What We Offer We encourage new and different ideas, creativity and contrarian thinking. You own your day-to-day management. What we care about is that we all hit our milestones. Competitive salary and equity in a growing, well-funded startup Excellent medical, dental, and vision coverage Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you We are looking forward to further shaping our culture with early team members. You'll have a chance to make your mark!

Job Description BLEW is excited to announce an opening for a Staff Scientist specializing in Environmental and Property Condition Assessments. In this role, you will be instrumental in managing projects that involve the assessment of both environmental conditions and physical property conditions for various projects across the United States. This a fantastic opportunity in the commercial real estate due diligence industry. Annual Salary Range: $70,000-$110,000 Responsibilities Conduct and write dual-scope(ESA/PCA) assignments, integrating environmental site assessments(Phase I's) and property condition assessments(PCAs). Provide solid recommendations and solutions to Managing Directors and clients while understanding the assessment’s potential impact on the transaction process. Oversee quality control throughout the project’s life cycle. Conduct site visits and lead fieldwork activities as necessary. Complete research (historical, regulatory, etc.). Communicate with client and subject site representatives. Conduct appropriate site reconnaissance. Data compilation and organization. Prepare quality supporting documentation (site figures, appendices, etc.). Other tasks as assigned by the Managing Director associated with report deliverable schedule and plan. Requirements Bachelor's degree in Environmental Science, Environmental Engineering, Architecture, or a related field. 5+ years of experience in environmental assessments and property condition assessments. Strong knowledge of, and experience with, Fannie Mae and Freddie Mac scopes of work is beneficial. Strong knowledge of, and experience with, HUD scopes of work is beneficial. Excellent verbal and written communication abilities. Strong analytical and problem-solving skills. Experience managing multiple projects simultaneously while meeting tight deadlines. Professional certifications, such as Certified Environmental Professional (CEP), Registered Architect(RA), or Professional Engineer(PE), are a plus. Radon & AHERA (Asbestos) certifications are a plus. Proficient in project management software, Microsoft Office Suite, and other relevant tools. Benefits 95% coverage of health benefits including Medical and Dental with optional family and/or dependent enrollment paid by employee at a group rate 50% company contribution towards Vision coverage Tuition reimbursement (up to $5,250 per year) 401(k) matching program: company match 100% of your deferrals up to 3% of your compensation, plus 50% of your deferrals over 3% not exceeding 5% of your compensation 100% employer paid Short-Term Disability with employee buy up options 100% employer paid Life Insurance Coverage with employee buy up options Paid parental leave Holiday pay Sick pay Paid vacations Possible year-end bonuses based on performance and tenure Company computer Relocation and Sign on Bonuses may apply

About Nudge Nudge's goal is to help the brain work better by creating a generalized product that can precisely stimulate and image the brain, entirely non-invasively. We aim to achieve this by developing cutting-edge ultrasound technology to treat neurological and psychiatric disorders, like addiction, and eventually, creating a mainstream consumer device that can modulate mood, focus, sleep, and more. To realize those ambitions, we're growing a scrappy, multidisciplinary, science and engineering team focused on making the best technology possible for interfacing with the whole brain, and a product that has the potential to improve people's daily lives more than any other. About the team The Research Team at Nudge is innovating on multiple frontiers in neuroscience and neurotechnology, and is primarily focused on developing ultrasound-based neuromodulation to treat conditions like depression, chronic pain and addiction as well as enhance the wellbeing of healthy people. We're also building the first scalable, portable hardware for noninvasive structural ultrasound-based imaging the quality of an MRI. The team is running human trials for neuromodulation and developing algorithms that will enable on-device imaging. About the role Work closely with the Head of Research and engineering team to build the capabilities for on-device ultrasound-based imaging. Develop algorithms for structural and functional ultrasound-based imaging Perform validation of in-silico ultrasound imaging methods with Nudge hardware in physical models and in vivo Contribute to the development of aberration correction techniques informed by ultrasound-based imaging About you 5+ years experience PhD or Postdoc in Bioengineering, Medical Imaging, Physics or equivalent Expertise in ultrasound physics and metrology Demonstrated history of exceptional contributions in your prior work experiences Expertise in one or more of: Full-waveform inversion imaging Functional transcranial doppler imaging Functional ultrasound imaging Machine learning experience a plus Compensation $140,000 - $230,000/year + equity Your salary may vary depending on multiple factors such as job-related knowledge, skills, and experience. #J-18808-Ljbffr

The Post-Training team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable. The Science of Post-training team is responsible for advancing the frontier of RLHF. We combine rigorous scientific experimentation with strong technical execution to drive progress in model alignment. Our goal is to develop insights that would make model training more robust and efficient. We contribute to core model deployments like GPT-4.1 and o3, but our main mandate is to pursue foundational research that will guide the trajectory of future model development. About the Role As a Research Scientist on the Science of Post-training team, you will be responsible for developing a theoretical and empirical understanding of post-training techniques. We're looking for people with a background in reinforcement learning research, who can iterate quickly and bring a rigorous scientific lens to training production-scale models. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and execute experiments to study the mechanics and efficacy of RL algorithms Develop new theoretical frameworks to explain and predict behavior of post-training systems Collaborate with cross-functional teams on the deployment and evaluation of safe, aligned models in production You might thrive in this role if: You have a strong foundation in computer science, statistics, machine learning, physics, robotics, or a similarly rigorous theoretical and empirical discipline You are excited to work at the intersection of scientific research and real-world deployment You value rapid iteration via simple, well-executed experimentation You are a strong programmer, who would feel comfortable engaging with low-level technical details About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology. #J-18808-Ljbffr

Salient is pioneering voice AI solutions to transform consumer loan servicing and compliance. Our initial focus: the $1.5T U.S. auto lending market. In under two years since our launch Salient has seen rapid market growth, including: Scaling to more than $10M in ARR Partnering with some of the largest consumer lenders in America Cash flow positive Raising $65m in funding from top-tier venture capital investors Interfacing with more than 2 million unique US consumers Processing over $150M in cash transactions Preventing $30M in fraud and 35k+ CFPB violations In-person office culture in San Francisco, CA About the Role We're looking for an Applied Research Scientist with expertise in Text-to-Speech (TTS) to help us push the boundaries of speech synthesis. You'll work on developing high-quality, low-latency TTS systems that power real-world applications. The ideal candidate combines deep modeling knowledge with a strong engineering mindset to deliver robust, scalable solutions. Responsibilities Perform any relevant engineering tasks related to model training and serving. E.g., data ingestion, data cleaning, evaluation Design and train high-quality, low-latency SOTA and TTS models for real-time agent deployment Integrate TTS into cascaded LLM+ASR systems; explore joint optimization and feedback loops Lead research efforts on prosody, speaker identity control, and expressiveness in speech synthesis Prototype and evaluate new architectures and training pipelines for high-fidelity voice generation Collaborate with infra and product teams to bring research into production Contribute to internal tooling for data processing, model training, and inference benchmarking Requirements Proven track record developing state of the art TTS systems or advanced degree in speech synthesis Strong modeling skills and experience training deep neural networks for speech synthesis Deep understanding of audio modeling, phoneme alignment, vocoders, and real-time inference challenges Ability to move from research to working code, this is a hands on role Comfortable working independently and collaboratively and defining your own roadmap in an ambiguous, fast-moving environment Ability to work 4 days a week from our San Francisco office (open to candidates willing to relocate) Nice to Have Familiarity with multilingual or code-switched TTS Experience with voice cloning, style transfer, or emotion conditioning in speech Contributions to academic publications or open-source projects in speech generation As an early-stage company building at the frontier of AI, we work with high intensity and commitment. While schedules can vary by role/team, many weeks will demand extra focus, flexibility and time particularly during major launches and high impact sprints. We're seeking those who are aligned to and able to commit to that expectation which includes 4 days per week in our San Francisco Office. #J-18808-Ljbffr

About Prima Mente Prima Mente's goal is to deeply understand the brain, to protect the brain from neurological disease and enhance the brain in health. We do this by generating our own data, building brain foundation models, and translating discovery to real clinical and research impact. Role focus - Hands On Research Direction Solve complex biological problems via robust high impact experimental design and critical judgements on project viability. Publish world-class scientific research papers. Drive foundational research in ML for biological problems, setting ambitious agendas and leading their execution. Conceptualize and develop novel foundation models, scaling them across massive, complex biological datasets. Lead high-impact experiments, effectively navigating signal-to-noise in large-scale biological data. Collaborate closely with interdisciplinary teams, bridging AI research, computational biology, and experimental scientists. Publish influential research in leading journals and conferences, establishing thought leadership in BioAI. Mentor researchers, building a vibrant, collaborative, and scientifically rigorous culture. Expected Growth In 1 month you will be responsible for: Deeply understanding our existing biological datasets, research infrastructure, and current foundation-model architecture. Formulating clear hypotheses and a prioritized roadmap for foundational model research, including immediate experimental directions. Establishing close relationships with interdisciplinary teams (ML engineers, computational biologists, experimental scientists), ensuring effective collaboration. In 3 months you directly own and have created: A prototype or early iteration of a novel AI foundation model specifically designed or fine-tuned for biological datasets. Initial experimental results demonstrating significant potential for improving predictive accuracy or biological insights, validating your chosen research direction. A clear research proposal and experimental framework presented internally. In 6 months you have: Delivered substantial progress on a state-of-the-art genomic foundation model, validated through rigorous benchmarking and demonstrating measurable biological or clinical impact. Authored (or prepared for submission) a manuscript targeting top-tier conferences or journals, clearly establishing the team as a thought leader in BioAI. Started mentoring junior team members, actively shaping the scientific and cultural growth of your research team. Built productive collaborations across internal and external teams, significantly contributing to the company's reputation and scientific credibility in AI-driven genomics. Why Join Us: Meaningful Impact: Contribute directly to research infrastructure that powers discoveries potentially impacting millions of lives. Innovation & Autonomy: Work at the forefront of AI and multi-omics, with the freedom to propose and implement state-of-the-art infrastructure solutions. Exceptional Team: Collaborate with talented colleagues from diverse backgrounds across ML, bioinformatics, and engineering. Growth Opportunities: Continuous learning and growth opportunities in a rapidly advancing technical field. Culture Insight What we are doing is extremely hard. Prima Mente is for great people. We are team players who appreciate challenges, want to be hands-on, and thrive on curiosity by throwing away assumptions. We are focused on excellence at pace and huge personal growth. We are strong communicators who are highly disciplined and rigorous. Prima Mente operates with a flat organizational structure. We gain and share knowledge by contributing to multiple opportunities. Leadership is given to those who show initiative and consistently deliver excellence. We arrange our lives so we can work in person as much as possible. Our Values Exceptional performance at exceptional pace The solutions we build demand uncompromising quality and rigour. The problems we are solving are grave and present. Inquisitive discovery We embrace curiosity and creativity. Every question is a path to a transformational breakthrough. Radical candour We practice unwavering honesty and transparency in all our challenges and interactions. Purposeful individuality Every individual in our team is celebrated for their identity, uniqueness, and experiences. We are invested in each one's bespoke personal development. Nurturing individuality will supercharge our collective purpose and spirit. Patient impact at scale We have a steadfast commitment to improve the health and well-being of patients globally. Every experiment run, every dataset analysed, and every innovation developed, is a step towards achieving a scalable impact. Who You Are You want to redefine what's possible at the frontier of AI and biology. You're intellectually curious, ambitious, and passionate about applying AI to biology. You thrive in interdisciplinary teams, possess an entrepreneurial spirit, and embrace the uncertainty and excitement of pioneering research. Necessary experience Experience of leading and building highly collaborative research teams. High agency with the ability to jump on any task as needed. Hands on end-to-end development of high impact publications that use ML methodologies to solve biological problems. Proven track record developing state-of-the-art ML models, ideally including transformers, diffusion models, or multimodal architectures. Experience applying ML to large multimodal biological datasets (genomics, transcriptomics, epigenomics, proteomics, single-cell data). Exceptional coding skills (Python, PyTorch, JAX, TensorFlow) and familiarity with scalable training frameworks. Experience managing large-scale distributed training across GPUs/TPUs. Background in generative AI, large language models, mechanistic interpretability, or reinforcement learning. Interview Process Our interview process is hard from the beginning, so please do come prepared to show us your strongest self. Marie is based in SF and Hannah in London - we are both available to support this process. We promise to communicate clearly about our process, look for your strengths, be transparent in our feedback and listen to your feedback - we are always learning. The interview steps are listed below. 1-3 are done remotely over video call. Our preference for 4-7 is in person, but remote is possible too. At stage 4 more information will be shared about the following steps. Screen with Marie or Hannah Meet Ravi CV Deep Dive Take Home Technical Challenge & Discussion Analysis Challenge with Ravi Systems Design & Live Coding Presentation of your work to the wider team #J-18808-Ljbffr

About sync. sync. is a team of artists, engineers, and scientists building foundation models to edit and modify people in video. Founded by the creators of Wav2lip and backed by legendary investors, including YC, Google, and visionaries Nat Friedman and Daniel Gross, we've raised 6 million dollars in our seed round to evolve how we create and consume media. Within months of launch our flagship lipsync API scaled to millions in revenue and powers video translation, dubbing, and dialogue replacement workflows for thousands of editors, developers, and businesses around the world. That's only the beginning, we're building a creative suite to give anyone Photoshop-like control over humans in video - zero-shot understanding and fine-grained editing of expressions, gestures, movement, identity, and more. Everyone has a story to tell, but not everyone's a storyteller - yet. We're looking for talented and driven individuals from all backgrounds to build inspired tools that amplify human creativity. About the role We're looking for an exceptional Research Scientist to help us build generative video models that understand and modify humans in video. You'll work directly with the creators of Wav2lip, pushing the boundaries of what's possible in fine-grained video control and video understanding. What you'll work on Design and scale cutting-edge generative models that can seamlessly control and edit different attributes of humans in video Pioneer new architectures for zero-shot video representation learning Explore novel problems and capabilities to push the limits of "what is possible" Tackle core challenges in precise video editing that large generative models struggle with Build primitives that capture and express human idiosyncrasies What you'll need 3+ years research experience in generative AI, computer vision, or deep learning Deep expertise in training generative models in PyTorch Curiosity and the drive to understand the unknown Proven record of implementing and adapting cutting-edge papers Proven ability to take research from concept to production Track record of breakthrough technical innovation Preferred qualifications Expertise in recent SOTA generative architectures (e.g. Diffusion) History working with face/human editing in video Notable publications or open-source contributions Expertise in model optimization and scalability Our goal is to keep the team lean, hungry, and shipping fast. These are the qualities we embody and look for: Raw intelligence: we tackle complex problems and push the boundaries of what's possible. Boundless curiosity: we're always learning, exploring new technologies, and questioning assumptions. Exceptional resolve: we persevere through challenges and never lose sight of our goals. High agency: we take ownership of our work and drive initiatives forward autonomously. Outlier hustle: we work smart and hard, going above and beyond to achieve extraordinary results. Obsessively data-driven: we base our decisions on solid data and measurable outcomes. Radical candor: we communicate openly and honestly, providing direct feedback to help each other grow. #J-18808-Ljbffr

Hedra is a pioneering generative media company backed by top investors at Index, A16Z, and Abstract Ventures. We're building Hedra Studio, a multimodal creation platform capable of control, emotion, and creative intelligence. At the core of Hedra Studio is our Character-3 foundation model, the first omnimodal model in production. Character-3 jointly reasons across image, text, and audio for more intelligent video generation - it's the next evolution of AI-driven content creation. Note: At Hedra, we're a team of hard-working, passionate individuals seeking to fundamentally change content and build a generational company together. You should have start-up experience and be a self-starter that is driven to build impactful products that change the status quo. The Hedra team is fully in-person in SF/NY with a shared love of solving hard problems using whiteboards. Overview: We are seeking a highly motivated Research Scientist to join our team and drive innovation in video generation and AI agents using 3D Variational Auto-encoders (3DVAE) and video diffusion models. The ideal candidate will have a strong background in machine learning, particularly in generative models, and a passion for pushing the boundaries of what's possible in AI. Responsibilities: Conduct cutting-edge research in video generation and AI agents, focusing on developing new architectures and algorithms for 3DVAE and video diffusion models. Collaborate with the team to integrate research findings into practical applications, ensuring models are suitable for deployment. Stay up-to-date with the latest developments in the field, such as advancements in diffusion models for video, and identify opportunities for innovation. Present research findings and results to the team and stakeholders, potentially contributing to publications in top-tier conferences or journals. Qualifications: PhD in Computer Science, Machine Learning, or a related field, with a focus on generative models. Extensive knowledge of deep learning, particularly VAEs and diffusion models, with experience in 3D data processing and representation, Proficiency in programming languages like Python, and familiarity with deep learning frameworks such as PyTorch or TensorFlow, essential for model development. Strong communication and collaboration skills, given the need to work with diverse teams and present complex research. A track record of publications in top-tier conferences or journals is a plus, reflecting research impact. This role is critical for advancing the state of the art, with a focus on developing new methods rather than applying existing ones, aligning with the startup's innovative goals. Benefits: Competitive compensation and equity 401k (no match) Healthcare (Silver PPO Medical, Vision, Dental) Lunch and snacks at the office We encourage you to apply even if you don't fully meet all the listed requirements; we value potential and diverse perspectives, and your unique skills could be a great asset to our team. #J-18808-Ljbffr

We are Genmo, a research lab dedicated to building open, state-of-the-art models for video generation towards unlocking the right brain of AGI. Join us in shaping the future of AI and pushing the boundaries of what's possible in video generation. Role overview: We are seeking an exceptional Research Scientist to join our team, focusing on developing cutting-edge diffusion models for text-to-video generation. In this role, you will be at the forefront of innovation, creating novel architectures and algorithms that transform written descriptions into stunning, coherent video content. Key responsibilities: Lead research initiatives in advanced diffusion models for text-to-video generation, focusing on improving visual quality, temporal consistency, and semantic fidelity Develop and implement state-of-the-art algorithms for translating textual descriptions into dynamic video content Design and conduct rigorous experiments to validate new ideas and evaluate model performance Collaborate with cross-functional teams to integrate research breakthroughs into our production pipeline Stay at the cutting edge of the field by regularly reviewing academic literature and attending top-tier conferences Contribute to the research community through high-quality publications and open-source contributions Mentor junior researchers and foster a culture of innovation within the research team Work closely with product teams to align research directions with user needs and market opportunities Qualifications: Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field Must have: Strong publication record in top-tier conferences (e.g., CVPR, ICCV, NeurIPS, ICML) with a focus on generative models, particularly diffusion models Extensive experience implementing and optimizing large-scale generative models for image or video tasks Deep understanding of state-of-the-art techniques in text-to-image and text-to-video generation Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow Excellent communication skills with the ability to explain complex technical concepts to diverse audiences Proven ability to work collaboratively in a team environment Ideal candidate will have: Postdoctoral or industrial research experience in generative AI for video Hands-on experience with text-to-video generation projects Expertise in other generative model architectures (e.g., GANs, VAEs) and their applications to video Experience working with large-scale datasets and distributed computing environments Track record of successful collaboration with product teams on technology transfers Familiarity with video codecs, compression techniques, and perceptual quality metrics Contributions to open-source projects in the field of generative AI Additional information The role is based in the Bay Area (San Francisco). Candidates are expected to be located near the Bay Area or open to relocation. Genmo is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law. Genmo, Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish. #J-18808-Ljbffr

Research Scientist / Machine Learning Scientist Type:Full-Time About the Role: The Clientis seeking a variety of Machine Learning Scientist to help advance how we evaluate and understand AI models. You'll help design and analyze experiments that uncover what makes models useful, trustworthy and capable through human preference signals. Your work will contribute to the scientific foundations of understanding AI at scale. This role is deeply interdisciplinary. You'll work closely with engineers, product teams, marketing and the broader research community to develop new methods for comparing models, analyzing preference data, and disentangling performance factors like style, reasoning, and robustness. Your work will inform both the public leaderboard and the tools we provide to model developers. If you're excited by open-ended questions, rigorous evaluation, and research that's grounded in real-world impact, you'll find a meaningful home here. We're looking for: • Hands-on experience training large-scale models, including reward models, preference models, and fine-tuning LLMs with methods like RLHF, DPO, and contrastive learning. • Strong foundation in ML and statistics, with a track record of designing novel training objectives, evaluation schemes, or statistical frameworks to improve model reliability and alignment. • Fluent in the full experimental stack, from dataset design and large-batch training to rigorous evaluation and ablation, with an eye for what scales to production. • Deeply collaborative mindset, working closely with engineers to productionize research insights and iterating with product teams to align modeling goals with user needs. Responsibilities: • Design and conduct experiments to evaluate AI model behavior across reasoning, style, robustness, and user preference dimensions • Develop new metrics, methodologies, and evaluation protocols that go beyond traditional benchmarks • Analyze large-scale human voting and interaction data to uncover insights into model performance and user preferences • Collaborate with engineers to implement and scale research findings into production systems • Prototype and test research ideas rapidly, balancing rigor with iteration speed • Author internal reports and external publications that contribute to the broader ML research community • Partner with model providers to shape evaluation questions and support responsible model testing • Contribute to the scientific integrity and transparency of the The Clientleaderboard and tools Who is The Client? Created by researchers from UC Berkeley's SkyLab,The Clientis an open platform where everyone can easily access, explore and interact with the world's leading AI models. By comparing them side by side and casting votes for the better response, the community helps shape a public leaderboard, making AI progress more transparent, and grounded in real-world usage. Why Join Us? Trusted by organizations like Google,OpenAI,Meta, xAI, and more,The Clientis rapidly becoming essential infrastructure for transparent, human-centered AI evaluation at scale. With over one million monthly users and growing developer adoption, our impact is helping guide the next generation of safe, aligned AI systems-grounded in open access and collective feedback. Our work is regularly referenced by industry leaders pushing the frontier of safe and reliable AI.Sundar Pichai,Jeff Dean,Elon Musk, and Sam Altman. • High Impact: Your work will be used daily by the world's most advanced AI labs. • Global Reach: Develop data infrastructure powering millions of real-world evaluations, influencing AI reliability across industries at the top-tier • Exceptional Team: We are a small team of top talent from Google, DeepMind, Discord,Vercel,UC Berkeley, and Stanford. Requirements: • PhD or equivalent research experience in Machine Learning, Natural Language Processing, Statistics, or a related field • Strong understanding of LLMs and modern deep learning architectures (e.g., Transformers, diffusion models, reinforcement learning with human feedback) Proficiency in Python and ML research libraries such as PyTorch, JAX, or TensorFlow • Demonstrated ability to design and analyze experiments with statistical rigor • Experience publishing research or working on open-source projects in ML, NLP, or AI evaluation • Comfortable working with real-world usage data and designing metrics beyond standard benchmarks • Ability to translate research questions into practical systems and collaborate across engineering and product teams • Passion for open science, reproducibility, and community-driven research What we offer: • The cash compensation for this position has not yet been finalized. Actual compensation will depend on job-related knowledge, skills, experience, and candidate location. • Competitive salary and meaningful equity • Comprehensive healthcare coverage (medical, dental, vision) • The opportunity to work on cutting-edge AI with a small, mission-driven team • A culture that values transparency, trust, and community impact Come help build the space where anyone can explore and help shape the future of AI. #J-18808-Ljbffr

Prima Mente's goal is to deeply understand the brain, to protect the brain from neurological disease and enhance the brain in health. We do this by generating our own data, building brain foundation models, and translating discovery to real clinical and research impact. Role focus - Hands On Research Direction Solve complex biological problems via robust high impact experimental design and critical judgements on project viability. Publish world-class scientific research papers. Drive foundational research in ML for biological problems, setting ambitious agendas and leading their execution. Conceptualize and develop novel foundation models, scaling them across massive, complex biological datasets. Lead high-impact experiments, effectively navigating signal-to-noise in large-scale biological data. Collaborate closely with interdisciplinary teams, bridging AI research, computational biology, and experimental scientists. Publish influential research in leading journals and conferences, establishing thought leadership in BioAI. Mentor researchers, building a vibrant, collaborative, and scientifically rigorous culture. Expected Growth In 1 month you will be responsible for: Deeply understanding our existing biological datasets, research infrastructure, and current foundation-model architecture. Formulating clear hypotheses and a prioritized roadmap for foundational model research, including immediate experimental directions. Establishing close relationships with interdisciplinary teams (ML engineers, computational biologists, experimental scientists), ensuring effective collaboration. In 3 months you directly own and have created: A prototype or early iteration of a novel AI foundation model specifically designed or fine-tuned for biological datasets. Initial experimental results demonstrating significant potential for improving predictive accuracy or biological insights, validating your chosen research direction. A clear research proposal and experimental framework presented internally. In 6 months you have: Delivered substantial progress on a state-of-the-art genomic foundation model, validated through rigorous benchmarking and demonstrating measurable biological or clinical impact. Authored (or prepared for submission) a manuscript targeting top-tier conferences or journals, clearly establishing the team as a thought leader in BioAI. Started mentoring junior team members, actively shaping the scientific and cultural growth of your research team. Built productive collaborations across internal and external teams, significantly contributing to the company's reputation and scientific credibility in AI-driven genomics. Why Join Us: Meaningful Impact: Contribute directly to research infrastructure that powers discoveries potentially impacting millions of lives. Innovation & Autonomy: Work at the forefront of AI and multi-omics, with the freedom to propose and implement state-of-the-art infrastructure solutions. Exceptional Team: Collaborate with talented colleagues from diverse backgrounds across ML, bioinformatics, and engineering. Growth Opportunities: Continuous learning and growth opportunities in a rapidly advancing technical field. Culture Insight What we are doing is extremely hard. Prima Mente is for great people. We are team players who appreciate challenges, want to be hands-on, and thrive on curiosity by throwing away assumptions. We are focused on excellence at pace and huge personal growth. We are strong communicators who are highly disciplined and rigorous. Prima Mente operates with a flat organizational structure. We gain and share knowledge by contributing to multiple opportunities. Leadership is given to those who show initiative and consistently deliver excellence. We arrange our lives so we can work in person as much as possible. Our Values Exceptional performance at exceptional pace The solutions we build demand uncompromising quality and rigour. The problems we are solving are grave and present. Inquisitive discovery We embrace curiosity and creativity. Every question is a path to a transformational breakthrough. Radical candour We practice unwavering honesty and transparency in all our challenges and interactions. Purposeful individuality Every individual in our team is celebrated for their identity, uniqueness, and experiences. We are invested in each one's bespoke personal development. Nurturing individuality will supercharge our collective purpose and spirit. Patient impact at scale We have a steadfast commitment to improve the health and well-being of patients globally. Every experiment run, every dataset analysed, and every innovation developed, is a step towards achieving a scalable impact. Who You Are You want to redefine what's possible at the frontier of AI and biology. You're intellectually curious, ambitious, and passionate about applying AI to biology. You thrive in interdisciplinary teams, possess an entrepreneurial spirit, and embrace the uncertainty and excitement of pioneering research. Necessary experience Experience of leading and building highly collaborative research teams. High agency with the ability to jump on any task as needed. Hands on end-to-end development of high impact publications that use ML methodologies to solve biological problems. Proven track record developing state-of-the-art ML models, ideally including transformers, diffusion models, or multimodal architectures. Experience applying ML to large multimodal biological datasets (genomics, transcriptomics, epigenomics, proteomics, single-cell data). Exceptional coding skills (Python, PyTorch, JAX, TensorFlow) and familiarity with scalable training frameworks. Experience managing large-scale distributed training across GPUs/TPUs. Background in generative AI, large language models, mechanistic interpretability, or reinforcement learning. Interview Process Our interview process is hard from the beginning, so please do come prepared to show us your strongest self. Marie is based in SF and Hannah in London - we are both available to support this process. We promise to communicate clearly about our process, look for your strengths, be transparent in our feedback and listen to your feedback - we are always learning. The interview steps are listed below. 1-3 are done remotely over video call. Our preference for 4-7 is in person, but remote is possible too. At stage 4 more information will be shared about the following steps. Screen with Marie or Hannah Meet Ravi CV Deep Dive Take Home Technical Challenge & Discussion Analysis Challenge with Ravi Systems Design & Live Coding Presentation of your work to the wider team #J-18808-Ljbffr

Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. We are looking for Research Scientists to develop and productionize advanced autonomy evaluations on our Frontier Red Team. Our goal is to develop and implement a gold standard of advanced autonomy evals to determine the AI Safety Level (ASL) of our models. This will have major implications for the way we train, deploy, and secure our models, as detailed in our Responsible Scaling Policy (RSP) . We believe that developing autonomy evals is one of the best ways to study increasingly capable and agentic models. If you've thought particularly hard about how models might be agentic and associated risks, and you've built an eval or experiment around it, we'd like to meet you. Please note: We will be prioritizing candidates who can start ASAP and can be based in either our San Francisco or London office. We're still iterating on the structure of our team. It is possible that this role might end up being the people manager of a few other individual contributors (ICs). If you would be interested in people management, you may express interest in the application. Responsibilities: Lead the end-to-end development of autonomy evals and research. This starts with risk and capability modeling, and includes designing, implementing, and regularly running these evals. Quickly iterate on experiments to evaluate autonomous capabilities and forecast future capabilities. Provide technical leadership to Research Engineers to scope + build scalable and secure infrastructure to quickly run large-scale experiments. Communicate the outcomes of the evaluations to relevant Anthropic teams, as well as policy stakeholders and research collaborators, where relevant. Collaborate with other projects on the Frontier Red Team, Alignment, and beyond to improve infrastructure and design safety techniques for autonomous capabilities. You may be a good fit if you: Have an ML background and experience leading experimental research on LLMs/multimodal models and/or agents Have strong Python-based engineering skills Are driven to find solutions to ambiguously scoped problems Design and run experiments and iterate quickly to solve machine learning problems Thrive in a collaborative environment (we love pair programming) Have experience training, working with, and prompting models The expected salary range for this position is: $280,000 - $425,000 USD Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Apply for this job * indicates a required field First Name * Last Name * Email * Phone Resume/CV Enter manually Accepted file types: pdf, doc, docx, txt, rtf (Optional) Personal Preferences * How do you pronounce your name? LinkedIn Profile Please ensure to provide either your LinkedIn profile or Resume, we require at least one of the two. Website Publications (e.g. Google Scholar) URL Are you open to working in-person in one of our offices 25% of the time? * Select... When is the earliest you would want to start working with us? Do you have any deadlines or timeline considerations we should be aware of? AI Policy for Application * Select... While we encourage people to use AI systems during their role to help them work faster and more effectively, please do not use AI assistants during the application process. We want to understand your personal interest in Anthropic without mediation through an AI system, and we also want to evaluate your non-AI-assisted communication skills. Please indicate 'Yes' if you have read and agree. Why Anthropic? * Why do you want to work at Anthropic? (We value this response highly - great answers are often 200-400 words.) What's your ideal breakdown of your time in a working week, in terms of hours or % per week spent on meetings, coding/running evals, reading papers, etc.? * Will you now or will you in the future require employment visa sponsorship to work in the country in which the job you're applying for is located? * Select... Do you require visa sponsorship? * Select... We are only hiring for the San Francisco office at this time. Will you be able to be based in the Bay Area and work from the office at least 2 days a week? * Select... If you are not already based here, are you open to relocation for this role? Additional Information Add a cover letter or anything else you want to share. Have you ever interviewed at Anthropic before? * Select... Voluntary Self-Identification For government reporting purposes, we ask candidates to respond to the below self-identification survey.Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in aconfidential file. As set forth in Anthropic's Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law. If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows: A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability. A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service. An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense. An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985. Select... 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If you want to learn more about the law or this form, visit the U.S. Department of Labor's Office of Federal Contract Compliance Programs (OFCCP) website at ***************** . How do you know if you have a disability? A disability is a condition that substantially limits one or more of your “major life activities.” If you have or have ever had such a condition, you are a person with a disability. Disabilities include, but are not limited to: Alcohol or other substance use disorder (not currently using drugs illegally) Autoimmune disorder, for example, lupus, fibromyalgia, rheumatoid arthritis, HIV/AIDS Blind or low vision Cancer (past or present) Cardiovascular or heart disease Celiac disease Cerebral palsy Deaf or serious difficulty hearing Diabetes Disfigurement, for example, disfigurement caused by burns, wounds, accidents, or congenital disorders Epilepsy or other seizure disorder Gastrointestinal disorders, for example, Crohn's Disease, irritable bowel syndrome Intellectual or developmental disability Mental health conditions, for example, depression, bipolar disorder, anxiety disorder, schizophrenia, PTSD Missing limbs or partially missing limbs Mobility impairment, benefiting from the use of a wheelchair, scooter, walker, leg brace(s) and/or other supports Nervous system condition, for example, migraine headaches, Parkinson's disease, multiple sclerosis (MS) Neurodivergence, for example, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities Partial or complete paralysis (any cause) Pulmonary or respiratory conditions, for example, tuberculosis, asthma, emphysema Short stature (dwarfism) Traumatic brain injury Disability Status Select... 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About the Team The Post-Training team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable. The Science of Post-training team is responsible for advancing the frontier of RLHF. We combine rigorous scientific experimentation with strong technical execution to drive progress in model alignment. Our goal is to develop insights that would make model training more robust and efficient. We contribute to core model deployments like GPT-4.1 and o3, but our main mandate is to pursue foundational research that will guide the trajectory of future model development. About the Role As a Research Scientist on the Science of Post-training team, you will be responsible for developing a theoretical and empirical understanding of post-training techniques. We're looking for people with a background in reinforcement learning research, who can iterate quickly and bring a rigorous scientific lens to training production-scale models. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and execute experiments to study the mechanics and efficacy of RL algorithms Develop new theoretical frameworks to explain and predict behavior of post-training systems Collaborate with cross-functional teams on the deployment and evaluation of safe, aligned models in production You might thrive in this role if: You have a strong foundation in computer science, statistics, machine learning, physics, robotics, or a similarly rigorous theoretical and empirical discipline You are excited to work at the intersection of scientific research and real-world deployment You value rapid iteration via simple, well-executed experimentation You are a strong programmer, who would feel comfortable engaging with low-level technical details About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI's Affirmative Action and Equal Employment Opportunity Policy Statement. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology. #J-18808-Ljbffr

At Imbue, we believe technology should be human-centered. In this role, you'll work with other scientists and engineers to build collaborative agentic products that help people build software. We're looking for impact-oriented people who want to help invent a new paradigm of programming using AI agents, with a focus on improving code output and the oversight of agents and software. Research Areas of Interest RL methods for LLMs Code verification, including techniques such as test generation and LLM-as-a-judge Reasoning agents Synthetic data generation You Will Lead research initiatives in AI-assisted software development, from zero to one. Able to create research questions that clarify the nature of the problem being solved, and coordinate a research program to successfully answer those questions. Extremely comfortable running ML experiments. Able to clearly communicate about your ideas and intuitions. Excited to mentor a small team of great research engineers. You Have A track record of high-quality papers, open-source projects, or equivalent accomplishments in industry. Experience with empirical research, with the ability to craft and execute on research projects that solve algorithmic and engineering problems. Great intuition with the ability to identify promising areas and avoid dead ends. A preference for fast, collaborative research efforts. 5+ years ML coding and/or research experience. Compensation and Benefits Generous compensation, equity, and benefits. Actively co-create and participate in a positive, intentional team culture. Frequent team events, dinners, off-sites, and hanging out. $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc. Compensation packages are highly variable based on a variety of factors. If your salary requirements fall outside of the stated range, we still encourage you to apply. The range for this role is $250,000-$500,000 cash, $1M-$5M in equity. How to apply All submissions are reviewed by a person, so we encourage you to include a cover letter. If you have any other work that you can showcase (specific publications, open source code, side projects, etc.), you should certainly include it! We try to reply either way within a week or two at most (usually much sooner). We know that talent comes from many backgrounds, and with many different skills and preferences. That's why we have a hiring process that gives you the ability to showcase yourself in a variety of different ways, depending on what feels best for you. Learn more about our full interview process here. About us Imbue builds AI systems that reason and code, enabling AI agents to accomplish larger goals and safely work in the real world. By using these agents extensively, we gain insights into improving both the capabilities of the underlying models and the interaction design for agents. We aim to rekindle the dream of the personal computer, where computers become truly intelligent tools that empower us, giving us freedom, dignity, and agency to pursue the things we love. #J-18808-Ljbffr

Who are we? Coastal Carbon is a seed-funded startup on a mission to create positive impact through earth observation and AI. Founded at the University of Waterloo by a team of PhDs and engineers, we're backed by some of the best AI and climate tech investors like HF0, Inovia Capital and Propeller Ventures, angels like James Tamplin (cofounder Firebase) and Sid Gorham (cofounder OpenTable, Granular), and partners like Amazon AWS and the United Nations. What do we do? We're building multimodal foundation models for the natural world. We believe there's more to the world than the internet + more to intelligence than memorizing the internet. Our models are trained on satellite remote sensing and real world ground truth data, and are used by our customers in nature conservation, carbon dioxide removal, and government to protect and positively impact our increasingly changing world. Our ultimate goal is to build AGI of the natural world. About the role We are looking for an AI Research Scientist to join our team and contribute to designing and building cutting-edge models. The role will involve: Research & Design: Deep understanding of current machine learning research. Proven track record of generating new ideas or enhancing existing ones in machine learning, evidenced by first-author publications or projects. Contribute to research that uncovers the semantics of large datasets, with a focus on earth observation and remote sensing data. Ability to independently manage and execute a research agenda, selecting impactful problems and conducting long-term projects autonomously. Implementation: Developing high-level proof-of-concept (POC) models. Experimenting with new state-of-the-art techniques to surpass existing models. Plan and execute innovative research and development to push the boundaries of current technology. Writing and Publication: Assisting in the preparation and writing of technical and scientific papers for publication. Demonstrated strong scientific communication/presentation skills. Requirements PhD degree in computer science, engineering, a related field, or equivalent experience. Proven track record of successful machine learning research projects 5+ years of experience in relevant jobs Strong scientific understanding of the field of generative AI Experience showing first-author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL) Location wise, strong preference for in-person in San Francisco. We are an entirely in-person team, but are willing to consider remote for exceptional candidates. Nice to have Proficiency in scripting languages such as Python, Bash, or PowerShell. Demonstrated experience with deep learning and transformer models. Familiarity with designing, training, and fine-tuning large models. Proficiency in frameworks like PyTorch or TensorFlow. Strong technical engineering skills. Previous experience in creating high-performance implementations of deep learning algorithms. Team player, willing to undertake various tasks to support the team. #J-18808-Ljbffr

Research Scientist, Frontier Red Team (CBRN, Biosecurity) About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. This team will intensively red-team models to test the most significant risks they might be capable of in areas such as biosecurity, cybersecurity risks, or autonomy. We believe that clear demonstrations can significantly advance technical research and mitigations, as well as identify effective policy interventions to promote and incentivize safety. As part of this team, you will lead research to baseline current models and test whether future frontier capabilities could cause significant harm. Day-to-day, you may decide you need to finetune a model to see whether it becomes superhuman in an eval you've designed; whiteboard a threat model with a national security expert; test a new training procedure or how a model uses a tool; or brief government, labs, and other research teams. Our goal is to see the frontier before we get there. Our CBRN workstream is hiring for a Research Scientist, with an emphasis on biosecurity risks (as outlined in our Responsible Scaling Policy ). By nature, this team will be an unusual combination of backgrounds. We are particularly looking for people with experience in these domains: Biosecurity: You're a biologist who's concerned about the implications of AI development. You're an academic who researches biosecurity defense. You have experience modeling biological phenomena or developing advanced threat modeling simulations. Science: You're an ML researcher who builds agents to augment chemistry or biology research. You've built a protein language model and you enjoyed looking through the embedding space. You're a team lead at an ML-for-drug discovery company. You've built software for astronauts or materials scientists. Evaluations: You've managed a large-scale benchmark development project, in AI or other domains. You have ideas about how AI and ML evaluations can be better. Do not rule yourself out if you do not fit one of those categories - it's plausible the people we're looking for do not fit any of the above! If you think about the most significant upsides and downsides of AI, and you can do good research to get glimpses of what those look like, please consider applying. Please note: We will only be considering candidates who can be based in the Bay Area for this role. We have a strong preference for candidates who can start ASAP, and ideally by May 2025. Responsibilities Independently lead research projects while collaborating with team members on larger initiatives Design, run, and analyze scientific experiments to advance our understanding of large language models Work with external partners to develop novel evaluations to accurately assess the biosecurity implications of our models Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic's safety mission Communicate our findings to external stakeholders, such as policymakers You may be a good fit if you Have one of: An advanced degree (MS or PhD) in the biological sciences (Molecular Biology, Computational Biology, Bioengineering) Significant professional experience in biology research (including wet-lab) Take pride in writing clean, well-documented code in Python that others can build upon Have a track record of using technical infrastructure to interface effectively with machine learning models Have familiarity with prompting and engineering large language models Are able to balance research goals with practical engineering constraints Have strong problem-solving skills and a results-oriented mindset Have excellent communication skills and ability to work in a collaborative environment Pick up slack, even if it goes outside your job description Prefer fast-moving collaborative projects to extensive solo efforts Care about the societal impacts of AI Strong candidates may also have experience with Wet lab experience in molecular biology Leading large projects with multiple external collaborators or stakeholders Developing evaluations or benchmarks for large language models Emerging technology policy, including in biosecurity or AI Representative projects Design and implement a new evaluation to test models for CBRN risks Develop a detailed threat model of CBRN risks, and identify how core bottlenecks can be resolved from further evaluations Prepare briefing materials to share the results of an evaluation run with external research groups The expected salary range for this position is: $280,000 - $425,000 USD Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Apply for this job * indicates a required field First Name * Last Name * Email * Phone Resume/CV Enter manually Accepted file types: pdf, doc, docx, txt, rtf (Optional) Personal Preferences * How do you pronounce your name? LinkedIn Profile Please ensure to provide either your LinkedIn profile or Resume, we require at least one of the two. Website Publications (e.g. Google Scholar) URL Are you open to working in-person in one of our offices 25% of the time? * Select... When is the earliest you would want to start working with us? Do you have any deadlines or timeline considerations we should be aware of? AI Policy for Application * Select... While we encourage people to use AI systems during their role to help them work faster and more effectively, please do not use AI assistants during the application process. We want to understand your personal interest in Anthropic without mediation through an AI system, and we also want to evaluate your non-AI-assisted communication skills. Please indicate 'Yes' if you have read and agree. Why Anthropic? * Why do you want to work at Anthropic? (We value this response highly - great answers are often 200-400 words.) Based on the types of biosecurity risks that the Frontier Red Team prioritizes (as outlined in our RSP), can you provide an example of a project the team should do that is in line with its mission? * Do you have any biology-related experience (computational biology, molecular biology, bioengineering, bioinformatics, etc.)? Select... What's your ideal breakdown of your time in a working week, in terms of hours or % per week spent on meetings, coding/running evals, reading papers, etc.? * Will you now or will you in the future require employment visa sponsorship to work in the country in which the job you're applying for is located? * Select... Do you require visa sponsorship? * Select... We are only hiring for the San Francisco office at this time. Will you be able to be based in the Bay Area and work from the office at least 2 days a week? * Select... If you are not already based here, are you open to relocation for this role? Additional Information Add a cover letter or anything else you want to share. Have you ever interviewed at Anthropic before? * Select... Voluntary Self-Identification For government reporting purposes, we ask candidates to respond to the below self-identification survey.Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in aconfidential file. As set forth in Anthropic's Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law. If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows: A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability. 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By applying to this role, you will be considered for Research Scientist roles across all teams at OpenAI. About the Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the team you work on, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company. We expect you to: Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects Be excited about OpenAI's approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI's Affirmative Action and Equal Employment Opportunity Policy Statement. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology. #J-18808-Ljbffr

Hedra is a pioneering generative media company backed by top investors at Index, A16Z, and Abstract Ventures. We're building Hedra Studio, a multimodal creation platform capable of control, emotion, and creative intelligence. At the core of Hedra Studio is our Character-3 foundation model, the first omnimodal model in production. Character-3 jointly reasons across image, text, and audio for more intelligent video generation - it's the next evolution of AI-driven content creation. Note : At Hedra, we're a team of hard-working, passionate individuals seeking to fundamentally change content and build a generational company together. You should have start-up experience and be a self-starter that is driven to build impactful products that change the status quo. You must be willing to work in-person in either NYC or SF. Overview : We are looking for an Applied Research Scientist with a specialization in model fine-tuning to join our team. This role involves taking our pre-trained 3DVAE and video diffusion models and adapting them to specific tasks or datasets to achieve optimal performance. The ideal candidate will have a deep understanding of transfer learning and fine-tuning techniques in the context of generative models. Responsibilities : Fine-tune pre-trained 3DVAE and video diffusion models for specific applications, such as generating videos for particular AI agent tasks, ensuring adaptability to new datasets. Develop and implement strategies for efficient model adaptation, such as data augmentation or transfer learning, to optimize performance. Evaluate and compare the performance of different fine-tuned models, using metrics relevant to video generation. Collaborate with the research team to understand the requirements and objectives of each fine-tuning task, ensuring alignment with business needs. Document and communicate findings to the team and stakeholders, facilitating knowledge sharing and decision-making. Qualifications : PhD or Master's degree in Computer Science, Machine Learning, or a related field, with a focus on model adaptation. Strong background in deep learning, with a focus on generative models, and experience with model fine-tuning and transfer learning techniques, crucial for adapting models to new tasks. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow, essential for implementation. Excellent problem-solving and analytical skills, given the need to evaluate and iterate on model performance. Good communication and teamwork skills, as collaboration is key in a startup environment. This role is focused on applying and refining existing models rather than developing new ones, ensuring practical deployment. Benefits : Competitive compensation and equity 401k (no match) Healthcare (Silver PPO Medical, Vision, Dental) Lunch and snacks at the office We encourage you to apply even if you don't fully meet all the listed requirements; we value potential and diverse perspectives, and your unique skills could be a great asset to our team. J-18808-Ljbffr Create a job alert for this search Applied Scientist • San Francisco, CA, US #J-18808-Ljbffr