Senior principal scientist jobs in Fremont, CA

About our team: Our team is dedicated to revolutionizing B2B e-commerce through the development of a groundbreaking AI search product. Leveraging cutting-edge LLM technology, we're creating a brand new AI search engine and streamline the entire purchasing process for B2B customers. Responsibilities ● Deliver full projects by defining the data structure, framework, design, and evaluation metrics for AI solution development and implementation. ● Develop and deploy Large Language Models (LLMs) to empower search and agent systems for a variety of applications. ● Identify new and upcoming product innovation areas by interacting with potential external and internal collaborators. ● Identify undefined problems in existing technology and engage stakeholders and leaders to address them. Qualifications ● PhD, Master's, or Bachelor's degree in Computer Science, Engineering, Mathematics, or related fields. ● Ability to implement and verify state-of-the-art NLP or Computer Vision algorithms. ● Experience in successfully applying machine learning approaches to real-world personalization problems. ● Experience with building large language models. ● Knowledge of statistical methods, with strong mathematical skills. ● Excellent problem-solving and programming skills in Python. The pay range for this position at commencement of employment is expected to be between $162,400/year and $266,000/year. However, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

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

⚡ Research Scientist - Data focus 💊 Foundation Models, AI Research Institute 🌎 San Francisco Bay Area, USA 💸 $200,000 - $350,000 salary + bonus Come join a revolutionary AI research lab in SF Bay Area that is poised to develop & publish high-impact breakthroughs in GenAI - across LLMs and Multimodal AI. As part of the team, you'll work at the intersection of data, large-scale training, and foundation model innovation. You will collaborate with world-class researchers, data scientists, and engineers to solve critical challenges in creating robust, scalable, and reasoning-capable LLMs. Your research will shape the way data is curated, processed, and leveraged to train the next generation of intelligent systems. Responsibilities: Lead research on data-centric approaches for LLMs, including pretraining corpus design, data valuation, and speculative decoding strategies. Develop pipelines to process challenging data sources into structured and reproducible training datasets. Build and optimize agentic data pipelines, integrating retrieval, self-curation, and multi-agent feedback for high-quality training and evaluation data. Collaborate with researchers on alignment and reasoning-focused training that leverage data-driven approaches for improving LLM capabilities. Prototype and deploy evaluation frameworks to measure data quality, coverage, and downstream impact on LLM reasoning. Publish findings at top-tier venues (e.g., NeurIPS, ICLR, ACL, EMNLP) and represent the institute at international conferences. Contribute to open-source tools, datasets, and benchmarks that advance the global foundation model research community. Requirements: Master's degree in Computer Science, Data Science, or a related technical field (PhD strongly preferred) Experience collecting and curating high-quality text data including multi-lingual data. Hands-on experience with large-scale dataset curation and preprocessing for ML/LLM training. Prior works synthesizing complex datasets. Code, math, and agentic data are higher priority Experience with ML infrastructure for scalable training, evaluation, and debugging. Experience at the intersection of data and post-training (RL/SFT) Proven ability to independently drive research questions related to data quality, scaling, or reasoning. Preferred Experience: Experience with retrieval-augmented generation (RAG), agentic data pipelines, or reasoning benchmarks. Contributions to speculative decoding, self-curation, or reinforcement learning from synthetic data. Background in knowledge graphs, semantic search, or indexing systems. Strong publication record in leading AI conferences. Prior contributions to open-source ML data tools or benchmarks. Prior work on speculative decoding/contributions to LLM serving engines Prior work on training LLM-as-a-judge Deep expertise with tokenization/training tokenizers Why apply: Opportunity to build out a new division at the forefront of AI innovation FAANG competitive salary & package Work alongside superstars from FAANG labs & leading AI companies 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 ************************

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. Ideally a background in Audio focused research. Alternatively Search, would also be highly advantageous. TC package of $1-1,5M with sizeable base salary & equity package. If that looks of interest, apply & Goliath will be in touch!

A frontier-stage research group is building a new class of AI systems designed to reason, plan, and act across the physical world. Their mission is to create intelligent agents capable of experimenting, engineering, and constructing in ways that dramatically accelerate scientific and industrial progress. This team combines deep technical pedigree with real-world wins at scale, including major government-funded initiatives. They operate where advanced model research meets robotics, simulation, and automated engineering systems, offering the kind of impact only possible when first-principles science meets ambitious execution. Joining means stepping into a high-ownership environment where you shape core capabilities end-to-end, influence the direction of physical-world intelligence, and help build technology the world has never seen before. Why This Role Is Compelling Work on cutting-edge reasoning, planning, and tool-use models that directly control autonomous engineering systems. Push the limits of SFT, RLHF, DPO, verifier-guided RL, and long-horizon planning in a setting where your research immediately translates into real-world capability. Operate in a high-velocity research culture with exceptional peers across agent systems, simulation, data, and complex toolchains. Have outsized ownership in a small team tackling one of the most ambitious technical problems of this decade. Role Overview The team is looking for an LLM Research Scientist to pioneer next-generation reasoning and agent architectures. Your work will span model design, alignment strategies, structured tool orchestration, and experimentation with agents interacting across real engineering workflows. This position blends deep research with hands-on systems integration, offering both autonomy and scope to lead foundational progress. Key Responsibilities Develop advanced models and prompting systems for planning, multi-step reasoning, and structured tool use. Lead training initiatives across SFT, RLHF/DPO, verifier-guided RL, and modular expert architectures to strengthen robustness and controllability. Define schemas, tool-calling strategies, policy constraints, safety mechanisms, and recovery pathways for agent behavior. Partner closely with engineering, simulation, and data teams to test, train, and evaluate models embedded in real production-like toolchains. Qualifications Significant experience in LLM research, agent reasoning models, or structured tool-use frameworks. Strong background working with SFT, RLHF, DPO, or reinforcement-learning-from-verification methods. Demonstrated ability to design, analyze, and improve long-horizon behaviors and decomposition strategies. Comfortable working across ML research, systems engineering, and real-world experimentation in a fast-moving environment. A track record of excellence and ownership in technically demanding domains.

💡 What if your next role let you design reinforcement learning systems that directly control real-world science -training agents that run experiments, tune physical tools, and accelerate discovery from months to days? 🚀 Our client - a hyper-talent-dense physical-AI startup backed by top-tier builders across frontier AI and deep tech - is hiring a Senior RL Research Scientist (San Francisco / Redwood City, In-Person). They're building Physical Superintelligence: AI that can ask any scientific question about the physical world and get a real answer in days, not years-by pairing large models with massive automated “experiment factories.” The role: 🎯 Own RL for real-world tool control and long-horizon workflows across biology, chemistry, materials, and robotics 🧪 Build RL environments grounded in physics, simulation, and digital twins-not toy benchmarks 🛡️ Design safe / constrained RL + verifier-integrated rewards to keep agents reliable in high-stakes domains 📈 Drive offline → online transitions and evaluation pipelines as agents learn from and act on real telemetry 🤝 Partner across LLM, agent systems, simulation, and physical-tooling teams to deploy policies into production workflows ⚙️ High-ownership algorithm + systems work where you shape the foundations of physical-AI autonomy Why join? 🌍 Work at the frontier of real-world impact-from multi-cancer early detection to general scientific discovery 🏭 Operate on a uniquely scaled platform: 20k+ sq ft automated facilities producing real experimental feedback loops 💰 Competitive salary + meaningful equity 🚀 Tiny, world-class team with a “best-person-you've-worked-with” talent bar 🏢 In-person, high-velocity environment with deep collaboration across SF + Redwood City 📩 Interested? Apply now

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

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.

Stage: Seed Team Size: < 10 We're looking for an Applied RS who can run the gamut of ML from infra to modeling and own the entire ML pipeline--taking advanced models into production. Our ideal candidate will be looking to build a co-pilot product from the ground up: helping to drive everything from key architectural decisions, applying SOTA methods, and shipping advanced production models in close collaboration with the founders. In key role, you will have real product ownership and the chance to influence not just what gets built, but how it gets built in a true 0->1 scenario. If you have 5+ years of experience in Machine Learning (infra and modeling) with 1+ years post-training LLM's and are thinking about starting your own company someday, this could be a great entry-way for you. Not only would you get real-world experience with something so early, but you'd get a chance to make a name for yourself with our investment team as well (making it much easier to get a chance to pitch us on your own idea in the future). About Greylock Greylock is a 1st-tier, early-stage venture capital firm that partners with exceptional founders at the seed and Series A stages. Our mission is to help realize rare potential - backing category-defining companies such as Figma, Anthropic, Ramp, Abnormal Security, Rubrik, Airbnb, LinkedIn, Roblox, Dropbox, and Coinbase. About the Greylock Recruiting Team As full-time, salaried employees of Greylock, our team provides free candidate referrals and introductions to our active portfolio companies. Combined, we bring over 125 years of in-house recruiting experience across startups and large-scale tech companies

Join the Frontier of AI-Driven Hardware Design Are you passionate about pushing the boundaries of artificial intelligence and eager to see your research power the next generation of computational hardware? We're a stealth-mode AI research and product lab on a mission to revolutionize chip design. Our team is reimagining how custom silicon is created-using advanced AI to dramatically accelerate and optimize the process, making ultra-efficient, domain-specific chips a reality. About Us Founded by leading minds from top universities and industry labs, our team brings together AI researchers and engineers from organizations like DeepMind, Meta, Apple, and Intel. We're backed by world-class investors, including renowned scientists, professors, and founders in the hardware and AI space. Here, you'll work alongside pioneers at the intersection of machine learning and hardware, building the intelligence layer for tomorrow's computing revolution. Your Role: Founding AI Researcher (ML) As a founding member of our technical team, you'll be at the heart of developing and deploying AI models that transform chip design. You'll tackle challenges like code generation, verification, architectural exploration, and multimodal reasoning-building multi-agent systems that can design, optimize, and verify real silicon. This is a hands-on, 0→1 opportunity: you'll own the full ML lifecycle, from data pipelines and model training to deployment and iteration, collaborating closely with hardware and product experts.You'll experiment at the bleeding edge of LLMs, reinforcement learning, and graph-based methods for EDA, defining how AI will shape the future of hardware What We're Looking For Academic Background: PhD in Computer Science, EECS, Mathematics, or a related field (or BS/MS with strong research engineering experience at leading labs or startups). AI/ML Expertise: Deep experience building end-to-end ML pipelines, including data curation, model training, and post-training using RL. Proven ability to take models from research to real-world deployment. Technical Skills: Hands-on with LLM/VLM deployment (vLLM, sg Lang, LM Studio, Ollama, etc.) and distributed training (QLoRA, ZeRO, CUDA, PyTorch Parallelism). Experience with RL post-training workflows, reward modeling, and environment design. Track record in code generation, reasoning, and tool use-especially in structured domains. Builder Mindset: Fast-moving, able to prototype, benchmark, and productionize ML pipelines with tight feedback loops. Passion: Excited to push the state-of-the-art in AI for real-world engineering challenges. Bonus Points: Experience at leading AI labs (OpenAI, DeepMind, Anthropic, etc.). Publications in top ML or EDA conferences. Background in hardware design or verification (not required). Why Join Us? Impact: Shape the future of AI-driven chip design from the ground up. Ownership: Significant autonomy and a meaningful equity stake. Growth: Work with a world-class team on cutting-edge challenges. Culture: Fast-paced, collaborative, and mission-driven environment. Ready to help define how AI will design the hardware of tomorrow? Apply now and join us at the frontier of AI and hardware innovation!

⚡ Research Scientist - Data focus 💊 Foundation Models, AI Research Institute 🌎 San Francisco Bay Area, USA 💸 $200,000 - $350,000 salary + bonus Come join a revolutionary AI research lab in SF Bay Area that is poised to develop & publish high-impact breakthroughs in GenAI - across LLMs and Multimodal AI. As part of the team, you'll work at the intersection of data, large-scale training, and foundation model innovation. You will collaborate with world-class researchers, data scientists, and engineers to solve critical challenges in creating robust, scalable, and reasoning-capable LLMs. Your research will shape the way data is curated, processed, and leveraged to train the next generation of intelligent systems. Responsibilities: Lead research on data-centric approaches for LLMs, including pretraining corpus design, data valuation, and speculative decoding strategies. Develop pipelines to process challenging data sources into structured and reproducible training datasets. Build and optimize agentic data pipelines, integrating retrieval, self-curation, and multi-agent feedback for high-quality training and evaluation data. Collaborate with researchers on alignment and reasoning-focused training that leverage data-driven approaches for improving LLM capabilities. Prototype and deploy evaluation frameworks to measure data quality, coverage, and downstream impact on LLM reasoning. Publish findings at top-tier venues (e.g., NeurIPS, ICLR, ACL, EMNLP) and represent the institute at international conferences. Contribute to open-source tools, datasets, and benchmarks that advance the global foundation model research community. Requirements: Master's degree in Computer Science, Data Science, or a related technical field (PhD strongly preferred) Experience collecting and curating high-quality text data including multi-lingual data. Hands-on experience with large-scale dataset curation and preprocessing for ML/LLM training. Prior works synthesizing complex datasets. Code, math, and agentic data are higher priority Experience with ML infrastructure for scalable training, evaluation, and debugging. Experience at the intersection of data and post-training (RL/SFT) Proven ability to independently drive research questions related to data quality, scaling, or reasoning. Preferred Experience: Experience with retrieval-augmented generation (RAG), agentic data pipelines, or reasoning benchmarks. Contributions to speculative decoding, self-curation, or reinforcement learning from synthetic data. Background in knowledge graphs, semantic search, or indexing systems. Strong publication record in leading AI conferences. Prior contributions to open-source ML data tools or benchmarks. Prior work on speculative decoding/contributions to LLM serving engines Prior work on training LLM-as-a-judge Deep expertise with tokenization/training tokenizers Why apply: Opportunity to build out a new division at the forefront of AI innovation FAANG competitive salary & package Work alongside superstars from FAANG labs & leading AI companies 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 ************************

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. Ideally a background in Audio focused research. Alternatively Search, would also be highly advantageous. TC package of $1-1,5M with sizeable base salary & equity package. If that looks of interest, apply & Goliath will be in touch!

💡 What if your next role let you push the frontier of LLM planning and tool-use-building agents that don't just talk about the physical world, but act in it to engineer, experiment, and manufacture autonomously? 🚀 Our client - a hyper-talent-dense physical-AI startup backed by top-tier builders across frontier AI and deep tech - is hiring a Senior LLM Research Scientist (San Francisco / Redwood City, In-Person). They're building Physical Superintelligence: AI systems with general physical ability-the capacity to experiment, engineer, or manufacture anything. Instead of only learning from static data, their models generate new data through automated real-world experimentation at massive scale. The role: 🧠 Develop planning, reasoning, and structured tool-use models that power autonomous engineering agents 🧪 Lead SFT + preference optimization work (RLHF / DPO) to push capability and reliability 🛡️ Build verifier-guided RL + safety constraints for robust long-horizon agent behavior 🔧 Design tool-calling schemas, recovery logic, and policy constraints so agents can operate real toolchains 🤝 Partner across agent systems, data infra, simulation, and tooling teams to train and evaluate in production workflows ⚙️ High-ownership research + systems integration on core models and agent behavior Why join? 🌍 Real-world impact at national scale-accelerating physical discovery, not just model training 🏭 A uniquely scaled platform for learning with automated experimental facilities generating new feedback loops 💰 Competitive salary + meaningful equity 🚀 Tiny, elite team with extremely high technical bar and low ego 🏢 In-person, high-velocity environment split across SF + Redwood City 📩 Interested? Apply now!

Senior RL Research Scientist / Reinforcement Learning Scientist Join a frontier AI team building systems that can act in the physical world, experimenting, optimizing, and controlling real processes through advanced ML, simulation, and automation. This group is pushing the boundaries of physical intelligence, backed by significant long-term funding and a mandate to invent from first principles. If you want to: Work on problems few teams in the world can touch Build RL systems that power real tools, workflows, and scientific processes Operate in a fast, high-ownership, deeply technical culture …this is the kind of role that defines a career. The Role You'll design and deploy reinforcement learning systems that control complex tools, optimize multi-step processes, and operate across high-fidelity simulations and digital twins. Expect hands-on research, real-world experimentation, and tight collaboration with teams across ML, simulation, and systems engineering. What You'll Do Build RL environments for tool control, workflow optimization, and long-horizon decision-making Develop safe and constrained RL methods, verifier-driven rewards, and offline to online training pipelines Create state/action representations and evaluation frameworks for reliable policy behavior Work with cross-functional researchers and engineers to deploy RL agents into real workflows What You Bring Strong background in RL, optimal control, or sequential decision-making Experience applying RL to complex simulated or physical systems Familiarity with safe/constrained RL, verifiers, or advanced evaluation pipelines Ability to design environments, rewards, and diagnostics at scale Comfort working across ML, simulation, and systems interfaces

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.

Stage: Seed Team Size: < 10 We're looking for an Applied RS who can run the gamut of ML from infra to modeling and own the entire ML pipeline--taking advanced models into production. Our ideal candidate will be looking to build a co-pilot product from the ground up: helping to drive everything from key architectural decisions, applying SOTA methods, and shipping advanced production models in close collaboration with the founders. In key role, you will have real product ownership and the chance to influence not just what gets built, but how it gets built in a true 0->1 scenario. If you have 5+ years of experience in Machine Learning (infra and modeling) with 1+ years post-training LLM's and are thinking about starting your own company someday, this could be a great entry-way for you. Not only would you get real-world experience with something so early, but you'd get a chance to make a name for yourself with our investment team as well (making it much easier to get a chance to pitch us on your own idea in the future). About Greylock Greylock is a 1st-tier, early-stage venture capital firm that partners with exceptional founders at the seed and Series A stages. Our mission is to help realize rare potential - backing category-defining companies such as Figma, Anthropic, Ramp, Abnormal Security, Rubrik, Airbnb, LinkedIn, Roblox, Dropbox, and Coinbase. About the Greylock Recruiting Team As full-time, salaried employees of Greylock, our team provides free candidate referrals and introductions to our active portfolio companies. Combined, we bring over 125 years of in-house recruiting experience across startups and large-scale tech companies

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

⚡ 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 ************************