Senior principal scientist jobs in Daly City, CA

About the Company We are a seed-stage AI company building the industry standard for evaluating and benchmarking large language models on real enterprise tasks. About the Role As a Research Scientist, you will develop new benchmarks, methodologies, and evaluation pipelines that shape how cutting-edge models are assessed, compared, and deployed in production environments. Your work will directly influence model selection and safety decisions across foundation model labs, high-growth AI product companies, and Fortune-scale enterprises. Responsibilities Benchmarking & Model Analysis Evaluate newly released models as they launch (e.g., Gemini, DeepSeek, etc.) Run large-scale assessment workflows using internal evaluation infrastructure Compare model performance across enterprise-grade task categories Design New Benchmarks from Scratch Identify high-value model application domains through research exploration Construct datasets, including labeling strategy and workforce coordination Write short “white-paper-style” summaries explaining benchmark purpose, method, and findings Advance Automated Evaluation Methodologies Improve systems for scoring generated text beyond standard metrics Explore research in reference-free, rubric-based, and human-aligned evaluation Develop new techniques for reliability, consistency, and repeatability Cross-functional Collaboration Work closely with engineering to scale evaluation infra Partner with customers to refine evaluation relevance and task fit Influence product direction through research insights Qualifications 0-3 years post-grad experience (Master's, PhD, or equivalent applied research) Publications, preprints, or demos showing cutting-edge work Experience with diffusion models, NLP, multimodal, or benchmarking work Ability to operate independently with ambiguity Clean, maintainable research codebases Candidates from: top engineering/research universities applied AI startups well-regarded research internships Required Skills Built or contributed to a benchmark or evaluation methodology Experience in enterprise task model evaluation Stanford / top lab adjacency (per their historical hiring success) Preferred Skills Wants to publish as primary motivation Purely academic with slow timelines Big-tech culture fit concerns (Meta / Google / Salesforce specifically noted-but case-by-case) Pay range and compensation package Base Salary: up to $250K depending on background Equity: typically 0.3% - 0.5%, flexibility for exceptional candidates Rapid equity refresh possible based on impact Equal Opportunity Statement Visa sponsorship available. Relocation support. Health & dental coverage. Lunch + dinner provided, snacks & coffee. Unlimited PTO. Weekly happy hours with community guests. Team events (bowling, hiking, rock climbing, etc.). Swag program (hats, etc.). Work Environment & Culture In-person, San Francisco HQ (required). Core hours: 9-5, some teammates extend voluntarily. Most team members work 1 weekend day per week (flexible). High-ownership, low-ego, collaborative. Live demos Mondays, team lunch Thursdays, community Fridays. Early-stage pace, applied focus-not academic publishing. Tech Environment (while research-focused, exposure beneficial) Backend: Python / Django. Frontend: React + TypeScript. Infra: AWS. Evaluation frameworks + internal tooling. Why This Role Is Unique The company already collaborates with foundation model labs, high-growth AI vertical product companies, and Fortune 500 enterprises (not publicly facing). ChatGPT Vals AI $5M seed raised, runway of 2+ years at current burn. Only one research scientist is being hired-true founding impact. Opportunity to define industry standards for model trust, reliability, and certification. Positioned to become the rating agency for generative AI.

Applied Scientist Package - > $200 - 250k Cash + Benefits A scaling, SOTA Generative AI Startup operating with a world class team (Founders have multiple prior exits) with talent from Open AI, IBM, MIT and several top orgs, focused on pioneering work and advancements in large language models (LLMs), code generation, and code translation. Their projects directly involve industry leading partners where they're applying advanced AI to solve meaningful, practical challenges with real-world impact. Broad Responsibilities: Design, execute, and analyze experiments with a high degree of independence Contribute to core models and frameworks Create high-quality datasets (both in-the-wild and synthetic) Perform literature reviews and implement new techniques from papers Contribute to publications, present at conferences and workshops, etc. Requirements: Ph.D. in Computer Science or another STEM subject Prior LLM research experience Comfortable programming in Python and familiar with frameworks such as PyTorch and HuggingFace Preferred Qualifications: Publications at peer-reviewed conferences such as NeurIPS, ICLR, ICML, etc. Experience with large-scale LLM training, particularly in a distributed computing environment Get in touch today for more details and immediate consideration / interview!

AI/ML Scientist - Build the Future of Physics AI- $250,000 to $275,000 Salary You will be part researcher, part builder, part pioneer, someone who thrives at the intersection of machine learning and physics based simulation. The platform is built on massively scalable, cloud native simulation technology that makes it possible to run thousands of high fidelity simulations quickly and easily. This foundation unlocks something big, enabling the generation of large scale datasets that power the next generation of ML models across industries. You will be on the front lines of building and productizing new machine learning approaches for physics based problems, from CFD to thermal simulation. Your work will not just live in a paper, it will deliver measurable value to customers, shape new product capabilities, and push the boundaries of what is possible in Physics AI. You know that rush when your work goes from experiment to production, when the models perform, the results hold up, and you can see the impact firsthand? That is what this role is about. Ready to shape the future of Physics AI? Let's talk. No up to date resume required.

Join a Leading Applied Research Lab Pushing the Boundaries of Reinforcement Learning Are you passionate about advancing the frontiers of reinforcement learning (RL)? An innovative AI research lab is seeking talented and ambitious scientists to shape the next generation of RL techniques-especially where they intersect with large models and environment generation. About the Role As an AI Research Scientist focused on RL, you will: Develop novel optimization-based methods for automated RL environment generation Establish baselines for evaluating the quality and diversity of RL environments Design infrastructure to create dynamic environments from historical datasets and agent evaluations Drive your own research agenda, contributing directly to the progress of our platform and the broader AI community What We're Looking For PhD (or equivalent experience) in machine learning, computer science or a related field Strong publication record and/or evidence of research impact (open source, deployed systems, etc.) Deep expertise in reinforcement learning and machine learning fundamentals Proficient in Python and at least one modern ML framework (such as PyTorch or JAX) Bonus Points Experience with post-training large language models (LLMs) Demonstrated software engineering skills Ability to communicate research findings effectively to both technical and non-technical audiences

San Francisco Insight are representing an early-stage AI startup who are fundamentally changing how media content is produced. They are building a cutting-edge multimodal AI platform capable of generating complex content across text, image, and audio. Key Responsibilities: Design, implement and evaluate novel deep learning architectures. Collaborate directly with the Eng team to translate research prototypes into prod systems. Drive the optimization of models for maximum scalability during training and inference. What we're looking for: PhD (or equivalent experience) in CompSci, ML, or similar. Proven record of developing and publishing research in Gen AI, particularly within video, image, or sequence modeling. Deep expertise in frameworks such as PyTorch/TensorFlow and extensive experience with large-scale transformer models. Please apply to hear more!

We're working with a San Francisco client that's got a research team of 50~ professionals and looking to further expand it. They are specifically looking to flesh out their Research Group by hiring a Research Scientist on a hybrid basis. They have seen $300M in a recent fund raise. Skills targeted: PhD in Physics/ Quantum Physics/ Theory/ Statistics/ Mathematics/ Computational Science or similarly related field. 2+ YoE working with AI Agents. Good exposure to LLMs. TC package of $1-1,5M with sizeable base salary & equity package. If that looks of interest, apply & Goliath will be in touch!

⚡ Research Scientists/Engineers (all levels) 🔍 Focus on Vision Data Infrastructure 🤖 Fundamental AI Research Institute 🌎 San Francisco Bay Area, USA 💸 $250,000 - $600,000 salary + annual bonus Come join one of the only research institutions globally with resources to compete with top AI companies =>10s of 1000s of GPUs to explore state-of-the-art research in LLMs, Multimodal and Agentic AI. Currently seeking AI talent with expertise in building scalable pipelines for vision data to support both image/video generative training and multi-modal alignment. You'll design high-performance pipelines for large-scale image and video datasets, enabling efficient pretraining, alignment, and simulation-based data generation. Responsibilities: Vision Data Sourcing & Curation Collect and organize image and video data from open datasets and the web. Handle data cleaning, filtering, deduplication, and metadata generation. Ensure ethical and compliant data collection at scale. Processing & Augmentation Build high-throughput pipelines for vision data preprocessing (frame extraction, resolution normalization, format conversion, latent caching). Implement GPU-accelerated augmentation and distributed data loading (WebDataset, TFRecords, Parquet). Synthetic & Simulation-Based Data Generation Use simulation tools (e.g., Unreal Engine 5, Isaac Sim, Unity) to generate high-quality synthetic vision data. Create specialized datasets for VLM training, visual reasoning, and agent interaction. Requirements: Strong experience with data engineering, computer vision, or machine learning infrastructure. Expertise in building and scaling ETL/data pipelines for large unstructured datasets. Proficiency with Python, PyTorch, and distributed data frameworks (e.g., Ray, Spark, Dask). Experience with WebDataset, TFRecords, Parquet, or similar high-throughput data formats. Familiarity with GPU-accelerated preprocessing, NVIDIA DALI, or equivalent systems. Understanding of image/video codecs, data compression, and cloud storage optimization. Preferred Experience: Prior work with simulation-based or synthetic data generation using Unreal Engine, Isaac Sim, or Unity. Experience curating datasets for multimodal or vision-language model training. Knowledge of data ethics, privacy, and compliance frameworks for large-scale AI datasets. Experience contributing to open datasets or data-centric AI research. Why apply: Opportunity to join a fast-growing core team that are already pushing AI breakthroughs Highly competitive salary package Work alongside ambitious and bright superstars from tech and academia Medical, Dental and Vision Insurance Relocation package available 🌎 San Francisco Bay Area, USA 📧 Interested in applying? Please click on the ‘Easy Apply' button or alternatively email me your resume at ************************

located in San Francisco, CA Responsibilities of the Scientist/Sr. Scientist-Stem Cell Biology/Embryology: Design and execute experiments in stem cell differentiation, organoid generation, and tissue engineering. Innovate then execute experiments to generate and differentiate human stem cells, develop functional assays, assess and interpret experimental workflows Perform mammalian embryo dissections, tissue isolations, and culture experiments to study and model developmental processes. Apply principles of developmental biology and embryology to guide tissue maturation and patterning. Collaborate with biomaterials and engineering teams to integrate cells and tissues. Develop and optimize protocols for reproducible tissue generation and maintenance. Test novel stem cell culture conditions, sort, screen, expand and differentiate hi PSCs according to latest protocols and newly developed approaches. Requirements of the Scientist/Sr. Scientist-Stem Cell Biology/Embryology: PhD in biological sciences, stem cell biology, genetics or related field. 2+ years hands-on expertise in stem cell culture (iPSCs/ESCs). Hands-on experience with mammalian embryos, including dissections and culture. Experience in molecular biology and strong problem solving skills.

Scientist, In Vivo Pharmacology - Permanent - Palo Alto, CA Where curiosity meets purpose-join us in shaping the future of science. Primary Responsibilities: Proclinical is seeking a highly motivated, dynamic Scientist to support in vivo research on our cutting-edge pipeline and discovery programs. You will be involved in the preparation and execution of murine animal experiments and the collation of data. The Scientist of In Vivo Pharmacology will: Preparation for and execution of translational experiments such as in vivo pharmacology and disease model experiments, including experiments in knockout and transgenic mice Animal handling during murine experiments, and handling of murine tissues resulting from animal experiments Management of relationships with third-party vendors on mouse breeding and shipping Identification, ordering, organization, storage, and proper disposal of laboratory reagents required for studies In collaboration with the Laboratory Biology team, aid in maintaining laboratory space and inventory Recording and filing data, preparing technical reports, and study summaries Report progress of projects in a timely and concise manner to supervisor May independently lead the development and implementation of new assays to support research projects; may independently execute experiments and perform data analyses of moderate complexity; may have responsibility for specific method or study. Occasionally provides assistance to and/or mentoring other technical staff, new research staff or interns Manages personal experimental timelines to meet project and personal goals Presents findings at the scientist, department, and site-level. Function as part of a collaborative team to support research needs Contribute to the optimal functioning of the research team, including implementation of new tools and technologies. Skills & Requirements: S. and 7+ years of laboratory experience (academic and/or industry) or M.S. with 5+ years of laboratory experience (academic and/or industry) Degree must be in a life sciences discipline, preferably cellular and/or molecular biology, biochemistry, and/or microbiology/immunology 3+ years of hands-on experience with in vivo murine research required, with mouse pharmacology and inflammation disease model experiments highly desired Experience in experimental techniques such as handling of animal tissue, cell culture, qRT-PCR, flow cytometry, and ELISAs/MSDs is required Experience in immunology research, including research with primary immune cells, would be valuable Must be highly organized, punctual, and precise both in regards to performing laboratory experiments as well as maintenance of the laboratory space. Ability to work independently and occasionally during non-traditional work hours as may be required by some experiments and will need to be comfortable in a laboratory and animal facility setting. Possesses effective problem-solving, organizational, and communication skills Experience with Microsoft software suite (Word, Excel, PowerPoint), and other commonly used computer applications (Zoom, MS Teams, Box, etc.) Clear and effective communicator across verbal, written, and interpersonal settings If you are interested in applying to this exciting opportunity, then please click 'Apply' or to speak to one of our specialists please request a call back at the top of this page. Proclinical is a leading life sciences recruiter focused on finding exceptional people and matching them with the finest positions across the globe. Proclinical is acting as an Employment Agency in relation to this vacancy. By submitting this application, you confirm that you've read and understood our privacy policy, which informs you how we process and safeguard your data - https://www.proclinical.com/privacy-policy

One of our partner company, are not just building AI-they're redefining what's possible at the nexus of physics, programming, and machine learning. As an Applied Scientist on their team, you'll tackle real-world scientific and coding challenges-developing novel reinforcement-learning algorithms and physics-informed models that accelerate breakthroughs in logic, coding, and semiconductor design. If you thrive on pushing the envelope of research and translating cutting-edge ideas into production-grade systems, this is your stage. What you'll do Prototype and validate new algorithms. Design, implement, and empirically evaluate novel RL, supervised, and unsupervised methods-especially those that leverage physics priors or logical constraints. Bridge research and production. Collaborate closely with ML Engineers and infrastructure teams to integrate experimental models into scalable pipelines, ensuring reproducibility, observability, and sub-second performance. Build robust experimentation platforms. Develop and maintain data-processing pipelines, training orchestration, and evaluation frameworks to accelerate iteration on large-scale experiments. Analyze and iterate. Dive deep into large datasets-experimental logs, simulation outputs, and user interaction traces-to diagnose model behavior, surface failure modes, and drive evidence-based improvements. Publish and present. Document findings in technical reports, contribute to open-source projects, and present work internally (and externally, when appropriate) to help shape the broader AI research community. What You Bring PhD or Master's in Computer Science, Applied Mathematics, Physics, Electrical Engineering, or a closely related field, with a strong focus on machine learning, reinforcement learning, or scientific computing. Hands-on experience developing and evaluating ML/RL algorithms-ideally demonstrated via publications, open-source contributions, or applied research projects. Proficiency in Python and deep-learning frameworks (PyTorch or TensorFlow), with solid coding practices for collaborative research. Excellent communication skills: able to distill complex technical ideas into clear narratives for both technical and non-technical audiences. Bonus Points (Not required, but great to have): Prior work on physics-informed neural networks, scientific simulations, or logic-based learning. Demonstrated expertise in reinforcement learning for combinatorial optimization, theorem proving, or code generation. Background in semiconductor design flows, EDA tools, or hardware-in-the-loop experimentation. What it's like here We're a rapidly growing, VC-backed startup where “raw talent and collaborative spirit over ego” isn't just a motto-it's how we work every day. You'll be surrounded by teammates who have built companies from zero to IPO, led teams at Google and Amazon, and earned medals in international science Olympiads. We value relentless curiosity, humble problem-solving, and a bias toward action. Logistics Redwood Shores, CA (U.S.) and Toronto, ON (Canada) Schedule: four days in our beautiful office, one day remote Visa Sponsorship: We welcome H-1B transfers and other employment-based visas

Senior Decision Scientist Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work Institute and recognized as a ‘Cool Vendor' and a ‘Vendor to Watch' by Gartner. Please visit Fractal | Intelligence for Imagination for more information about Fractal Position Overview: Fractal is looking for a proactive and driven Senior Decision Scientist to join our Decision Science Consulting team in the San Francisco, CA area. In this role, you will help power measurable outcomes for leading technology organizations, leveraging cutting edge GenAI, Data Science, Engineering and Behavioral Science capabilities This is a perfect opportunity for someone, who is looking to combine best-in-class data science and analytics skills, strong problem-solving, effective communication and thought leadership to help our clients solve their most strategic business problems Responsibilities: Drive business decision making by deeply analyzing clickstream and other structured data, building machine learning/ statistical models to uncover actionable insights, and developing presentations to communicate the findings and recommendations Manage project roadmap by discussing potential analytics ideas, prioritizing based on estimated benefit vs. effort, documenting and planning for risks and blockers and periodically sharing status updates Contribute to the analytical foundations by documenting data and business understanding, sharing knowledge with broader team and coming up with new opportunities such as automating repetitive tasks, researching and applying new approaches/ techniques and bringing in ideas from other disciplines such as consumer psychology, brand, economics, competitive analysis, etc. Qualifications: Bachelors or equivalent experience in statistics, computer science, engineering, informatics, data science, or related field; additional business degree is a plus 8+ years of data science/ analytics experience with demonstrable hands-on expertise 3+ years of leading complex projects working with (or supervising) analysts, data scientists, AI engineers, designers, etc. Familiarity or natural interest towards management activities (project management, product management, team management) is strongly preferred Excellent communication and presentation skills are a must Strong proficiency with data manipulation is required (SQL + Python) Strong familiarity with ML development and testing in Python is required Must display strong learning agility to know the latest and greatest techniques across Statistics, ML and GenAI (Preferred) Demonstrated experience working with digital marketing functions e.g. purchase funnel optimization, digital product enhancement, email/ push marketing, etc. Hands-on experience in one, or more of the following is strongly preferred: regression, classification, clustering, time series forecasting, NLP Familairity with Adobe Analytics and Snowflake is a plus Salary Range: $130,000 - $155,000 (bonus and benefit eligible) Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Join a Leading Applied Research Lab Pushing the Boundaries of Reinforcement Learning Are you passionate about advancing the frontiers of reinforcement learning (RL)? An innovative AI research lab is seeking talented and ambitious scientists to shape the next generation of RL techniques-especially where they intersect with large models and environment generation. About the Role As an AI Research Scientist focused on RL, you will: Develop novel optimization-based methods for automated RL environment generation Establish baselines for evaluating the quality and diversity of RL environments Design infrastructure to create dynamic environments from historical datasets and agent evaluations Drive your own research agenda, contributing directly to the progress of our platform and the broader AI community What We're Looking For PhD (or equivalent experience) in machine learning, computer science or a related field Strong publication record and/or evidence of research impact (open source, deployed systems, etc.) Deep expertise in reinforcement learning and machine learning fundamentals Proficient in Python and at least one modern ML framework (such as PyTorch or JAX) Bonus Points Experience with post-training large language models (LLMs) Demonstrated software engineering skills Ability to communicate research findings effectively to both technical and non-technical audiences

Applied Scientist Package - > $200 - 250k Cash + Benefits A scaling, SOTA Generative AI Startup operating with a world class team (Founders have multiple prior exits) with talent from Open AI, IBM, MIT and several top orgs, focused on pioneering work and advancements in large language models (LLMs), code generation, and code translation. Their projects directly involve industry leading partners where they're applying advanced AI to solve meaningful, practical challenges with real-world impact. Broad Responsibilities: Design, execute, and analyze experiments with a high degree of independence Contribute to core models and frameworks Create high-quality datasets (both in-the-wild and synthetic) Perform literature reviews and implement new techniques from papers Contribute to publications, present at conferences and workshops, etc. Requirements: Ph.D. in Computer Science or another STEM subject Prior LLM research experience Comfortable programming in Python and familiar with frameworks such as PyTorch and HuggingFace Preferred Qualifications: Publications at peer-reviewed conferences such as NeurIPS, ICLR, ICML, etc. Experience with large-scale LLM training, particularly in a distributed computing environment Get in touch today for more details and immediate consideration / interview!

About the Company We are a seed-stage AI company building the industry standard for evaluating and benchmarking large language models on real enterprise tasks. About the Role As a Research Scientist, you will develop new benchmarks, methodologies, and evaluation pipelines that shape how cutting-edge models are assessed, compared, and deployed in production environments. Your work will directly influence model selection and safety decisions across foundation model labs, high-growth AI product companies, and Fortune-scale enterprises. Responsibilities Benchmarking & Model Analysis Evaluate newly released models as they launch (e.g., Gemini, DeepSeek, etc.) Run large-scale assessment workflows using internal evaluation infrastructure Compare model performance across enterprise-grade task categories Design New Benchmarks from Scratch Identify high-value model application domains through research exploration Construct datasets, including labeling strategy and workforce coordination Write short “white-paper-style” summaries explaining benchmark purpose, method, and findings Advance Automated Evaluation Methodologies Improve systems for scoring generated text beyond standard metrics Explore research in reference-free, rubric-based, and human-aligned evaluation Develop new techniques for reliability, consistency, and repeatability Cross-functional Collaboration Work closely with engineering to scale evaluation infra Partner with customers to refine evaluation relevance and task fit Influence product direction through research insights Qualifications 0-3 years post-grad experience (Master's, PhD, or equivalent applied research) Publications, preprints, or demos showing cutting-edge work Experience with diffusion models, NLP, multimodal, or benchmarking work Ability to operate independently with ambiguity Clean, maintainable research codebases Candidates from: top engineering/research universities applied AI startups well-regarded research internships Required Skills Built or contributed to a benchmark or evaluation methodology Experience in enterprise task model evaluation Stanford / top lab adjacency (per their historical hiring success) Preferred Skills Wants to publish as primary motivation Purely academic with slow timelines Big-tech culture fit concerns (Meta / Google / Salesforce specifically noted-but case-by-case) Pay range and compensation package Base Salary: up to $250K depending on background Equity: typically 0.3% - 0.5%, flexibility for exceptional candidates Rapid equity refresh possible based on impact Equal Opportunity Statement Visa sponsorship available. Relocation support. Health & dental coverage. Lunch + dinner provided, snacks & coffee. Unlimited PTO. Weekly happy hours with community guests. Team events (bowling, hiking, rock climbing, etc.). Swag program (hats, etc.). Work Environment & Culture In-person, San Francisco HQ (required). Core hours: 9-5, some teammates extend voluntarily. Most team members work 1 weekend day per week (flexible). High-ownership, low-ego, collaborative. Live demos Mondays, team lunch Thursdays, community Fridays. Early-stage pace, applied focus-not academic publishing. Tech Environment (while research-focused, exposure beneficial) Backend: Python / Django. Frontend: React + TypeScript. Infra: AWS. Evaluation frameworks + internal tooling. Why This Role Is Unique The company already collaborates with foundation model labs, high-growth AI vertical product companies, and Fortune 500 enterprises (not publicly facing). ChatGPT Vals AI $5M seed raised, runway of 2+ years at current burn. Only one research scientist is being hired-true founding impact. Opportunity to define industry standards for model trust, reliability, and certification. Positioned to become the rating agency for generative AI.

We're working with a San Francisco client that's got a research team of 50~ professionals and looking to further expand it. They are specifically looking to flesh out their Research Group by hiring a Research Scientist on a hybrid basis. They have seen $300M in a recent fund raise. Skills targeted: PhD in Physics/ Quantum Physics/ Theory/ Statistics/ Mathematics/ Computational Science or similarly related field. 2+ YoE working with AI Agents. Good exposure to LLMs. TC package of $1-1,5M with sizeable base salary & equity package. If that looks of interest, apply & Goliath will be in touch!

San Francisco Insight are representing an early-stage AI startup who are fundamentally changing how media content is produced. They are building a cutting-edge multimodal AI platform capable of generating complex content across text, image, and audio. Key Responsibilities: Design, implement and evaluate novel deep learning architectures. Collaborate directly with the Eng team to translate research prototypes into prod systems. Drive the optimization of models for maximum scalability during training and inference. What we're looking for: PhD (or equivalent experience) in CompSci, ML, or similar. Proven record of developing and publishing research in Gen AI, particularly within video, image, or sequence modeling. Deep expertise in frameworks such as PyTorch/TensorFlow and extensive experience with large-scale transformer models. Please apply to hear more!

located in San Francisco, CA Responsibilities of the Scientist/Sr. Scientist-Stem Cell Biology/Embryology: Design and execute experiments in stem cell differentiation, organoid generation, and tissue engineering. Innovate then execute experiments to generate and differentiate human stem cells, develop functional assays, assess and interpret experimental workflows Perform mammalian embryo dissections, tissue isolations, and culture experiments to study and model developmental processes. Apply principles of developmental biology and embryology to guide tissue maturation and patterning. Collaborate with biomaterials and engineering teams to integrate cells and tissues. Develop and optimize protocols for reproducible tissue generation and maintenance. Test novel stem cell culture conditions, sort, screen, expand and differentiate hi PSCs according to latest protocols and newly developed approaches. Requirements of the Scientist/Sr. Scientist-Stem Cell Biology/Embryology: PhD in biological sciences, stem cell biology, genetics or related field. 2+ years hands-on expertise in stem cell culture (iPSCs/ESCs). Hands-on experience with mammalian embryos, including dissections and culture. Experience in molecular biology and strong problem solving skills.

Applied Scientist Package - > $200 - 250k Cash + Benefits A scaling, SOTA Generative AI Startup operating with a world class team (Founders have multiple prior exits) with talent from Open AI, IBM, MIT and several top orgs, focused on pioneering work and advancements in large language models (LLMs), code generation, and code translation. Their projects directly involve industry leading partners where they're applying advanced AI to solve meaningful, practical challenges with real-world impact. Broad Responsibilities: Design, execute, and analyze experiments with a high degree of independence Contribute to core models and frameworks Create high-quality datasets (both in-the-wild and synthetic) Perform literature reviews and implement new techniques from papers Contribute to publications, present at conferences and workshops, etc. Requirements: Ph.D. in Computer Science or another STEM subject Prior LLM research experience Comfortable programming in Python and familiar with frameworks such as PyTorch and HuggingFace Preferred Qualifications: Publications at peer-reviewed conferences such as NeurIPS, ICLR, ICML, etc. Experience with large-scale LLM training, particularly in a distributed computing environment Get in touch today for more details and immediate consideration / interview!

Join a Leading Applied Research Lab Pushing the Boundaries of Reinforcement Learning Are you passionate about advancing the frontiers of reinforcement learning (RL)? An innovative AI research lab is seeking talented and ambitious scientists to shape the next generation of RL techniques-especially where they intersect with large models and environment generation. About the Role As an AI Research Scientist focused on RL, you will: Develop novel optimization-based methods for automated RL environment generation Establish baselines for evaluating the quality and diversity of RL environments Design infrastructure to create dynamic environments from historical datasets and agent evaluations Drive your own research agenda, contributing directly to the progress of our platform and the broader AI community What We're Looking For PhD (or equivalent experience) in machine learning, computer science or a related field Strong publication record and/or evidence of research impact (open source, deployed systems, etc.) Deep expertise in reinforcement learning and machine learning fundamentals Proficient in Python and at least one modern ML framework (such as PyTorch or JAX) Bonus Points Experience with post-training large language models (LLMs) Demonstrated software engineering skills Ability to communicate research findings effectively to both technical and non-technical audiences