Scientist jobs in Alameda, CA

Senior LLM Research Scientist We're representing a cutting-edge AI organization building autonomous systems that can reason, plan, and interact with the physical world. This is a chance to join a small, elite research team pushing the frontier of LLM-driven autonomy. ⭐ The Opportunity You'll lead research that powers intelligent agents capable of long-horizon reasoning, structured tool-use, and real-world decision-making. This is deep ML research with immediate, tangible impact. What You'll Work On Building LLM reasoning and planning frameworks Designing structured tool-use, memory, reflection, and multi-step workflows Developing safe, robust policies for autonomous systems Training and evaluating models across real engineering and scientific tasks Collaborating with systems, simulation, and infrastructure experts What We're Looking For Strong research background in LLMs, reasoning, or agents Experience with SFT, RLHF/DPO, verifier-guided RL, or related training techniques Ability to design and evaluate long-horizon behaviors Comfort working in a fast, interdisciplinary R&D environment Why Join Build models that control real physical-world systems, NOT just simulations Massive scope for autonomy, creativity, and impact Competitive compensation + meaningful ownership

Senior LLM Research Scientist We're representing a cutting-edge AI organization building autonomous systems that can reason, plan, and interact with the physical world. This is a chance to join a small, elite research team pushing the frontier of LLM-driven autonomy. ⭐ The Opportunity You'll lead research that powers intelligent agents capable of long-horizon reasoning, structured tool-use, and real-world decision-making. This is deep ML research with immediate, tangible impact. What You'll Work On Building LLM reasoning and planning frameworks Designing structured tool-use, memory, reflection, and multi-step workflows Developing safe, robust policies for autonomous systems Training and evaluating models across real engineering and scientific tasks Collaborating with systems, simulation, and infrastructure experts What We're Looking For Strong research background in LLMs, reasoning, or agents Experience with SFT, RLHF/DPO, verifier-guided RL, or related training techniques Ability to design and evaluate long-horizon behaviors Comfort working in a fast, interdisciplinary R&D environment Why Join Build models that control real physical-world systems, NOT just simulations Massive scope for autonomy, creativity, and impact Competitive compensation + meaningful ownership

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

Title: AI Research Scientist Responsibilities: Design, execute, and analyze machine learning experiments, establishing strong baselines and selecting appropriate evaluation metrics. Stay up to date with the latest AI research; identify, adapt, and validate novel techniques for company-specific use cases. Define rigorous evaluation protocols, including offline metrics, user studies, and adversarial (red team) testing to ensure statistical soundness. Specify data and annotation requirements; develop annotation guidelines and oversee quality control processes. Collaborate closely with domain experts, product managers, and engineering teams to refine problem statements and operational constraints. Develop reusable research assets such as datasets, modular code components, evaluation suites, and comprehensive documentation. Work alongside ML Engineers to optimize training and inference pipelines, ensuring seamless integration into production systems. Contribute to academic publications and represent the company in research communities, as needed. Educational Qualifications: Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field is strongly preferred. Candidates with a master's degree and exceptional research or industry experience will also be considered. Industry Experience: 3-5 years of experience in AI/ML research roles, ideally in applied or product-focused environments. Demonstrated success in delivering research-driven solutions that have been deployed in production. Experience collaborating in cross-functional teams across research, engineering, and product. Publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ACL, CVPR) are a plus. Technical Skills: Strong foundational knowledge in machine learning and deep learning algorithms. Hands-on experience with PEFT/LoRA, adapters, fine-tuning techniques, and RLHF/RLAIF (e.g., PPO, DPO, GRPO). Ability to read, implement, and adapt state-of-the-art research papers to real-world use cases. Proficiency in hypothesis-driven experimentation, ablation studies, and statistically sound evaluations. Advanced programming skills in Python (preferred), C++, or Java. Experience with deep learning frameworks such as PyTorch, Hugging Face, NumPy, etc. Strong mathematical foundations in probability, linear algebra, and calculus. Domain expertise in one or more areas: natural language processing (NLP), symbolic reasoning, speech processing, etc. Ability to translate research insights into roadmaps, technical specifications, and product improvements. AI Research Scientist | Machine Learning | Deep Learning | Natural Language Processing | LLM | Hybrid | San Jose, CA

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.

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 $196,500/year and $325,500/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.

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

Creospan is a growing tech collective of makers, shakers, and problem solvers, offering solutions today that will propel businesses into a better tomorrow. “Tomorrow's ideas, built today!” In addition to being able to work alongside equally brilliant and motivated developers, our consultants appreciate the opportunity to learn and apply new skills and methodologies to different clients and industries. ******NO C2C/3RD PARTY, LOOKING FOR W2 CANDIDATES ONLY, must be able to work in the US without sponsorship now or in the future*** Summary: The main function of the Data Scientist is to produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Job Responsibilities: • Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement. • Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data. • Generate and test hypotheses and analyze and interpret the results of product experiments. • Work with product engineers to translate prototypes into new products, services, and features and provide guidelines for large-scale implementation. • Provide Business Intelligence (BI) and data visualization support, which includes, but limited to support for the online customer service dashboards and other ad-hoc requests requiring data analysis and visual support. Skills: • Experienced in either programming languages such as Python and/or R, big data tools such as Hadoop, or data visualization tools such as Tableau. • The ability to communicate effectively in writing, including conveying complex information and promoting in-depth engagement on course topics. • Experience working with large datasets. Education/Experience: • Master of Science degree in computer science or in a relevant field.

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

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!

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

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.

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

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.