Scientist jobs in Fairfield, CA

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

Senior Research Scientist - San Francisco or Redwood City A company who are building AI systems with general physical ability are looking for Senior Reinforcement Learning Research Scientist to build reinforcement learning systems that drive real-world experimentation and tool orchestration. What Will I be Doing: Create and maintain RL environments for optimizing tools, experiments, and process workflows using both simulations and digital twins. Develop safe RL strategies, reward structures integrated with verifiers, and frameworks for moving from offline training to robust online behavior. Define state and action representations and enforce constraints for reliable, long-horizon decision-making. Partner with LLM researchers, agent engineers, and simulation teams to integrate RL agents into live experimental systems. What We're Looking For: Expertise in reinforcement learning, optimal control, or sequential decision-making, with experience applying RL to complex real or simulated systems. Familiarity with safe RL, constrained RL, verifier/detector integration, or multi-step policy evaluation frameworks. Demonstrated ability to build RL environments, design reward structures, and diagnose policy behavior at scale. Comfortable working across ML, simulation, systems engineering, and physical-toolchain interfaces in a fast-paced research environment. What's in It for Me: $200-$300k and meaningful equity Ownership of cutting-edge RL systems deployed in real-world experimental workflows Work at the cutting edge of AI, robotics, and experimental science Contribute to building the world's first physical superintelligence Apply now for immediate consideration!

⚡ 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 ************************

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.

Employment Type: Full-time Available Positions: 1 Application Deadline: Dec 22, 2025 The LCMS Principal Scientist will be responsible for supporting non-GLP, GLP (non-clinical), and GCLP (clinical) projects. The role is responsible for supporting lab operations in a non-GLP area. Key Activities Independently conduct LC-MS method development for biologics (e.g., ADC, mAb, protein, peptide, oligonucleotide, etc.) in support of developability assessment, comparability assessment, in-depth characterisation, biotransformation, and CQA-related analysis. Present and interpret data internally and/or externally as needed. Serve as Subject Matter Expert (SME) for the LCMS platform. Serve as the Principal Investigator responsible for interaction with the client from the study design to scheduling, conducting, reporting, and transferring data. Ensure responsiveness to the client, timely delivery, and overall customer satisfaction. Provide oversight of the laboratory, mentor junior staff, and collaborate to keep improving operational excellence. Assist in establishing and improving policies, procedures, work instructions and SOPs. Understand and adhere to corporate standards regarding code of conduct and Environmental Health & Safety (EHS). Perform other related duties as assigned. Preferred Skills Supervisory experience in both project and talent (people) management is preferred. Ability to work independently and pay close attention to details. Educations & Experience PhD, M.S., in Chemistry, Biochemistry or related scientific fields required, including a minimum of 4+(Ph.D.) or 9+ (Master's) years of CRO/Pharma/Biotech experience. Hands-on experience with high-resolution LCMS method development and in-depth characterization. Are you looking for your next opportunity? We can help. Finding a great opportunity that fosters growth, a great culture, and leadership opportunities can be difficult. Top Quality Recruitment (TQR) connects professionals with leadership opportunities across the Packaging, Food and Beverage, Medical Devices, and Biotechnology industries. With 50+ years of experience, we believe in one-to-one communication and finding the best candidate/employer match possible. TQR is an equal-opportunity employer that encourages diversity. We will consider all applications. Accommodation for applicants with disabilities is available upon request. Are you looking to hire? Get started here: ****************************************************** See hiring advice: ******************************************* See all available opportunities: ******************************************* We thank all applicants for their interest and appreciate the time and effort involved; however, due to the large volume of resumes received only those candidates selected for an interview will be contacted. Please attached your resume to your application. Job ID: 8083

Staff Data Scientist | San Francisco | $250K-$300K + Equity We're partnering with one of the fastest-growing AI companies in the world to hire a Staff Data Scientist. Backed by over $230M from top-tier investors and already valued at over $1B, they've secured customers that include some of the most recognizable names in tech. Their AI platform powers millions of daily interactions and is quickly becoming the enterprise standard for conversational AI. In this role, you'll bring rigorous analytics and experimentation leadership that directly shapes product strategy and company performance. What you'll do: Drive deep-dive analyses on user behavior, product performance, and growth drivers Design and interpret A/B tests to measure product impact at scale Build scalable data models, pipelines, and dashboards for company-wide use Partner with Product and Engineering to embed experimentation best practices Evaluate ML models, ensuring business relevance, performance, and trade-off clarity What we're looking for: 5+ years in data science or product analytics at scale (consumer or marketplace preferred) Advanced SQL and Python skills, with strong foundations in statistics and experimental design Proven record of designing, running, and analyzing large-scale experiments Ability to analyze and reason about ML models (classification, recommendation, LLMs) Strong communicator with a track record of influencing cross-functional teams If you're excited by the sound of this challenge- apply today and we'll be in touch.

Amber Bio is a biotechnology company pioneering new gene editing modalities using multi-kilobase edits to reach previously undruggable patient populations. Founded by pioneers in the CRISPR field from leading institutions for gene editing research, the company is developing a first-of-its-kind RNA editing platform that can correct thousands of bases at once, thereby correcting genetic mutations safely and reversibly. If you are interested in building a new frontier in genetic medicine, we welcome you to apply. Job Description: Research Associate III/ Senior Research Associate (Biodesigner), Assay Development / Bioanalytical Development Position Overview: The Research Associate III/ Senior Research Associate in Assay Development and Bioanalytical Development will play a critical role in the development, qualification, and validation of bioanalytical methods to support our RNA editing programs. The successful candidate will work under the guidance of an assay development scientist to develop custom assays for the analysis of samples, including AAVs, cells, and tissues. This role also involves drafting key documents such as Standard Operating Procedures (SOPs) and method development reports. Key Responsibilities: Method Development, Qualification, and Validation: Support the development, qualification, and validation of bioanalytical methods in accordance with regulatory guidelines. Develop, optimize, and execute robust bioanalytical methods for the characterization, release, and stability testing of Amber's gene therapy. Sample Analysis: Support drug absorption, distribution, metabolism, and excretion studies. Perform analysis of AAVs, cells, and tissues to support various stages of research and development. Lead efforts to streamline and optimize sample storage and processing, as well as establishing and maintaining critical reagent stocks and cell banks. Documentation Reporting: Draft and review key documents such as SOPs, method development, and sample analysis reports. Maintain accurate and detailed records of all experiments and analyses. Collaboration & Communication Collaborate with manufacturing and preclinical teams to support pipeline needs. Communicate and present findings clearly to internal stakeholders. Qualifications: B.A./B.S. or M.S. in Molecular Biology, Biochemistry, Analytical Chemistry, or a related field. 3+ years of experience in bioanalytical and assay development in the biotechnology or pharmaceutical industry. Demonstrated strong proficiency in a wide range of molecular biology techniques such as molecular cloning, DNA/RNA extractions, RT-qPCR, dd PCR, and ELISA. Experience with cell-based assays and detection methods such as fluorescence, luminescence, and ECL. Hands-on experience using laboratory automated systems (e.g., liquid handlers, extraction robotics, etc.). Background in RNA-based therapies is highly desirable. Experience writing SOPs and reports supporting IND filings (e.g. development, qualification sample analysis reports, etc.) Knowledge of FDA and ICH guidelines for method development, qualification, and validation. Prior history in compiling and analyzing data and generating reports that are routinely presented to project teams. Ability to work effectively in a collaborative, fast-paced environment. Preference will be given to those who display: High motivation, with a strong work ethic and dedication to generating impact. Attention to detail, with the ability to extract deep insights from data. Ability to go from ideation to data in an independent fashion. Long-term personal vision with defined career goals. Team-oriented thinking. Demonstrated excellence in small team environments, including a “no task is too small” attitude. If you have a passion for advancing gene editing technologies and desire to be part of a pioneering biotech company, we encourage you to apply and join our ambitious team. Please apply directly through LinkedIn. Amber Bio is an equal-opportunity employer and encourages applications from candidates of diverse backgrounds. We value diversity and are committed to creating an inclusive and supportive work environment for all employees.

We're working with a Series A health tech start-up pioneering a revolutionary approach to healthcare AI, developing neurosymbolic systems that combine statistical learning with structured medical knowledge. Their technology is being adopted by leading health systems and insurers to enhance patient outcomes through advanced predictive analytics. We're seeking Machine Learning Engineers who excel at the intersection of data science, modeling, and software engineering. You'll design and implement models that extract insights from longitudinal healthcare data, balancing analytical rigor, interpretability, and scalability. This role offers a unique opportunity to tackle foundational modeling challenges in healthcare, where your contributions will directly influence clinical, actuarial, and policy decisions. Key Responsibilities Develop predictive models to forecast disease progression, healthcare utilization, and costs using temporal clinical data (claims, EHR, laboratory results, pharmacy records) Design interpretable and explainable ML solutions that earn the trust of clinicians, actuaries, and healthcare decision-makers Research and prototype innovative approaches leveraging both classical and modern machine learning techniques Build robust, scalable ML pipelines for training, validation, and deployment in distributed computing environments Collaborate cross-functionally with data engineers, clinicians, and product teams to ensure models address real-world healthcare needs Communicate findings and methodologies effectively through visualizations, documentation, and technical presentations Required Qualifications Strong foundation in statistical modeling, machine learning, or data science, with preference for experience in temporal or longitudinal data analysis Proficiency in Python and ML frameworks (PyTorch, JAX, NumPyro, PyMC, etc.) Proven track record of transitioning models from research prototypes to production systems Experience with probabilistic methods, survival analysis, or Bayesian inference (highly valued) Bonus Qualifications Experience working with clinical data and healthcare terminologies (ICD, CPT, SNOMED CT, LOINC) Background in actuarial modeling, claims forecasting, or risk adjustment methodologies

We are seeking a PhD-level Clinical Scientist to support the Biologics License Application (BLA) submission for a Breakthrough Therapy-designated biologic targeting a neurodegenerative rare disease. This role will contribute to late-stage clinical development, supporting clinical data interpretation, regulatory documentation, and cross-functional collaboration as the program advances toward potential approval. Key Responsibilities Support late-stage clinical development and BLA submission activities Interpret and synthesize clinical efficacy, safety, and biomarker data in pediatric populations Author and review clinical sections of regulatory documents (Modules 2 and 5) Collaborate cross-functionally with Regulatory, Clinical Operations, Biostatistics, and Medical Affairs Support FDA interactions and regulatory meetings as needed Qualifications PhD in a life sciences discipline 5+ years of clinical development experience in biotech or pharma Experience supporting late-stage programs and regulatory submissions (BLA/NDA/MAA) Strong scientific writing and cross-functional collaboration skills Experience in rare disease, pediatric, neurodegenerative, or biologics programs preferred Why This Role This is an opportunity to contribute to a Breakthrough Therapy-designated biologic at a critical regulatory milestone, advancing a program aimed at addressing serious unmet need in pediatric neurodegenerative disease.

Key Responsibilities Design and productionize models for opportunity scanning, anomaly detection, and significant change detection across CRM, streaming, ecommerce, and social data. Define and tune alerting logic (thresholds, SLOs, precision/recall) to minimize noise while surfacing high-value marketing actions. Partner with marketing, product, and data engineering to operationalize insights into campaigns, playbooks, and automated workflows, with clear monitoring and experimentation. Required Qualifications Strong proficiency in Python (pandas, NumPy, scikit-learn; plus experience with PySpark or similar for large-scale data) and SQL on modern warehouses (e.g., BigQuery, Snowflake, Redshift). Hands-on experience with time-series modeling and anomaly / changepoint / significant-movement detection(e.g., STL decomposition, EWMA/CUSUM, Bayesian/prophet-style models, isolation forests, robust statistics). Experience building and deploying production ML pipelines (batch and/or streaming), including feature engineering, model training, CI/CD, and monitoring for performance and data drift. Solid background in statistics and experimentation: hypothesis testing, power analysis, A/B testing frameworks, uplift/propensity modeling, and basic causal inference techniques. Familiarity with cloud platforms (GCP/AWS/Azure), orchestration tools (e.g., Airflow/Prefect), and dashboarding/visualization tools to expose alerts and model outputs to business users.

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 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 ************************

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

Staff Data Scientist | San Francisco | $250K-$300K + Equity We're partnering with one of the fastest-growing AI companies in the world to hire a Staff Data Scientist. Backed by over $230M from top-tier investors and already valued at over $1B, they've secured customers that include some of the most recognizable names in tech. Their AI platform powers millions of daily interactions and is quickly becoming the enterprise standard for conversational AI. In this role, you'll bring rigorous analytics and experimentation leadership that directly shapes product strategy and company performance. What you'll do: Drive deep-dive analyses on user behavior, product performance, and growth drivers Design and interpret A/B tests to measure product impact at scale Build scalable data models, pipelines, and dashboards for company-wide use Partner with Product and Engineering to embed experimentation best practices Evaluate ML models, ensuring business relevance, performance, and trade-off clarity What we're looking for: 5+ years in data science or product analytics at scale (consumer or marketplace preferred) Advanced SQL and Python skills, with strong foundations in statistics and experimental design Proven record of designing, running, and analyzing large-scale experiments Ability to analyze and reason about ML models (classification, recommendation, LLMs) Strong communicator with a track record of influencing cross-functional teams If you're excited by the sound of this challenge- apply today and we'll be in touch.

Amber Bio is a biotechnology company pioneering new gene editing modalities using multi-kilobase edits to reach previously undruggable patient populations. Founded by pioneers in the CRISPR field from leading institutions for gene editing research, the company is developing a first-of-its-kind RNA editing platform that can correct thousands of bases at once, thereby correcting genetic mutations safely and reversibly. If you are interested in building a new frontier in genetic medicine, we welcome you to apply. Job Description: Research Associate III/ Senior Research Associate (Biodesigner), Assay Development / Bioanalytical Development Position Overview: The Research Associate III/ Senior Research Associate in Assay Development and Bioanalytical Development will play a critical role in the development, qualification, and validation of bioanalytical methods to support our RNA editing programs. The successful candidate will work under the guidance of an assay development scientist to develop custom assays for the analysis of samples, including AAVs, cells, and tissues. This role also involves drafting key documents such as Standard Operating Procedures (SOPs) and method development reports. Key Responsibilities: Method Development, Qualification, and Validation: Support the development, qualification, and validation of bioanalytical methods in accordance with regulatory guidelines. Develop, optimize, and execute robust bioanalytical methods for the characterization, release, and stability testing of Amber's gene therapy. Sample Analysis: Support drug absorption, distribution, metabolism, and excretion studies. Perform analysis of AAVs, cells, and tissues to support various stages of research and development. Lead efforts to streamline and optimize sample storage and processing, as well as establishing and maintaining critical reagent stocks and cell banks. Documentation Reporting: Draft and review key documents such as SOPs, method development, and sample analysis reports. Maintain accurate and detailed records of all experiments and analyses. Collaboration & Communication Collaborate with manufacturing and preclinical teams to support pipeline needs. Communicate and present findings clearly to internal stakeholders. Qualifications: B.A./B.S. or M.S. in Molecular Biology, Biochemistry, Analytical Chemistry, or a related field. 3+ years of experience in bioanalytical and assay development in the biotechnology or pharmaceutical industry. Demonstrated strong proficiency in a wide range of molecular biology techniques such as molecular cloning, DNA/RNA extractions, RT-qPCR, dd PCR, and ELISA. Experience with cell-based assays and detection methods such as fluorescence, luminescence, and ECL. Hands-on experience using laboratory automated systems (e.g., liquid handlers, extraction robotics, etc.). Background in RNA-based therapies is highly desirable. Experience writing SOPs and reports supporting IND filings (e.g. development, qualification sample analysis reports, etc.) Knowledge of FDA and ICH guidelines for method development, qualification, and validation. Prior history in compiling and analyzing data and generating reports that are routinely presented to project teams. Ability to work effectively in a collaborative, fast-paced environment. Preference will be given to those who display: High motivation, with a strong work ethic and dedication to generating impact. Attention to detail, with the ability to extract deep insights from data. Ability to go from ideation to data in an independent fashion. Long-term personal vision with defined career goals. Team-oriented thinking. Demonstrated excellence in small team environments, including a “no task is too small” attitude. If you have a passion for advancing gene editing technologies and desire to be part of a pioneering biotech company, we encourage you to apply and join our ambitious team. Please apply directly through LinkedIn. Amber Bio is an equal-opportunity employer and encourages applications from candidates of diverse backgrounds. We value diversity and are committed to creating an inclusive and supportive work environment for all employees.

Key Responsibilities Design and productionize models for opportunity scanning, anomaly detection, and significant change detection across CRM, streaming, ecommerce, and social data. Define and tune alerting logic (thresholds, SLOs, precision/recall) to minimize noise while surfacing high-value marketing actions. Partner with marketing, product, and data engineering to operationalize insights into campaigns, playbooks, and automated workflows, with clear monitoring and experimentation. Required Qualifications Strong proficiency in Python (pandas, NumPy, scikit-learn; plus experience with PySpark or similar for large-scale data) and SQL on modern warehouses (e.g., BigQuery, Snowflake, Redshift). Hands-on experience with time-series modeling and anomaly / changepoint / significant-movement detection(e.g., STL decomposition, EWMA/CUSUM, Bayesian/prophet-style models, isolation forests, robust statistics). Experience building and deploying production ML pipelines (batch and/or streaming), including feature engineering, model training, CI/CD, and monitoring for performance and data drift. Solid background in statistics and experimentation: hypothesis testing, power analysis, A/B testing frameworks, uplift/propensity modeling, and basic causal inference techniques. Familiarity with cloud platforms (GCP/AWS/Azure), orchestration tools (e.g., Airflow/Prefect), and dashboarding/visualization tools to expose alerts and model outputs to business users.

Amber Bio is a biotechnology company pioneering new gene editing modalities using multi-kilobase edits to reach previously undruggable patient populations. Founded by pioneers in the CRISPR field from leading institutions for gene editing research, the company is developing a first-of-its-kind RNA editing platform that can correct thousands of bases at once, thereby correcting genetic mutations safely and reversibly. If you are interested in building a new frontier in genetic medicine, we welcome you to apply. Job Description: High-Throughput Screening Research Associate II, III (Biodesigner II, III) Responsibilities: Perform massively parallel reporter assays and high-throughput screens across diverse cellular contexts using cellular and molecular readouts. Develop and execute molecular biology workflows such as vector design and cloning, DNA/RNA extraction, RT-PCR, qPCR, and next-generation sequencing. Support cell culture activities and experiments in multiple cell lines, at small and large scales. Design and execute cell-based assays (AAV/lentiviral transduction, transfection, flow cytometry, immunostaining, and other plate reader assays). Engineer and characterize cell-based systems using synthetic biology tools and techniques. Conduct and troubleshoot experiments, independently and in collaboration with colleagues, to optimize screening throughput, sensitivity, and specificity. Proactively troubleshoot technical issues and recommend potential corrective actions based on personal observations and literature searches. Prepare summaries of data and present internally to colleagues and management. Draft SOPs, follow protocols, diligently document experimental data in lab notebooks, and organize and maintain electronic work records. Author scientific reports and data summaries. Collaborate with cross-functional teams to meet project goals, bridging early discovery with high-throughput screens to nominate and optimize candidates for further characterization. Qualifications: Bachelor's or Master's degree in Biology, Biochemistry, Chemical Engineering, Biological Engineering, or a related field. At least 2 years of industry wet lab experience. Mammalian cell culture experience (culturing, transfecting and transducing cells, and DNA/RNA purification from cells). Molecular biology expertise (vector design and cloning, qPCR, primer and probe design, DNA/RNA extraction workflows) Critical thinker with excellent communication skills who thrives in a multidisciplinary, fast-paced team environment. Strong written and verbal communication skills. Preference will be given to those who display: High throughput screening assay development in an industry setting. High motivation, with a strong work ethic and dedication to generating impact. Attention to detail, with the ability to extract deep insights from data. First-principles thinking, and an ability to refine one's intuition based on additional data. Ability to go from ideation to data in an independent fashion. Long-term personal vision with defined career goals. High EQ with team-oriented thinking. Experience with pooled, high-throughput screens using next-generation sequencing-based readouts, and/or preparing screening plasmid libraries from synthesized oligo arrays. Experience with CRISPR-Cas systems and/or gene editing and delivery technologies. Experience preparing next-generation sequencing libraries (Illumina, PacBio, and/or Nanopore platforms). If you have a passion for advancing gene editing technologies and desire to be part of a pioneering biotech company, we encourage you to apply and join our ambitious team. Please apply directly through LinkedIn. Amber Bio is an equal-opportunity employer and encourages applications from candidates of diverse backgrounds. We value diversity and are committed to creating an inclusive and supportive work environment for all employees.