Research associate jobs in Milpitas, CA

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

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

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

⚡ 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: 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.

100% ONSITE IN SOUTH SAN FRANCISCO CA PAY: $54-$59/hr REQUIRED: BS/MS with 1 year of LC-MS (QQQ) experience or a fresh PhD with the right LC-MS experience if they are a good fit and seem motivated. Degree in chemistry, pharmacology or other related fields. Pharmaceutical industry setting with a focus on mass spectrometry.• Prior industry experience in drug discovery/development is preferred. In-depth understanding of PK, TK and PK/PD studies and corresponding bioanalytical assays as well as in vitro characterization assays is highly desired. Hands-on experience with QQQ (SCIEX), qTOF (Agilent, Bruker, SCIEX) and/or Orbitrap (Thermo) mass spectrometers is highly desired. Hands-on experience with automated liquid handling systems is highly desired. Hands-on experience with oligonucleotide analysis is highly desired. Job Description: The Quantitative, Translational ADME Sciences (QTAS) department at Client is seeking a highly motivated scientist to join the Biologics bioanalysis, characterization, and proteomics group. The main function of this position is to develop and implement LC/MS (liquid chromatography/mass spectrometry)-based bioanalysis and in vitro characterization assays for Client biologics entities. The successful candidate will be experienced in the development, optimization and implementation of Client and routine LC/MS-based bioanalytical methods to support in vivo PK, TK, and PK/PD studies as well as in vitro stability characterization of therapeutic proteins, peptides, and oligonucleotides. The candidate will be responsible for sample preparation, method development, bioanalytical assay operations, data analysis, report generation, and data presentation. Key tasks and responsibilities: • Operate and maintain LC/MS instruments to generate high-quality experimental data. • Perform affinity purification of therapeutic proteins (including but not limited to monoclonal and bispecific antibodies, antibody drug conjugates, antibody-si RNA conjugates, and fusion proteins) from biological matrices. • Analyze data and maintain detailed, accurate and comprehensive study documentation in electronic laboratory notebooks. • Facilitate assay optimization and implementation to ensure laboratory capacity and data quality. • Communicate data interpretation internally and externally.

, December 8th-May 31st, 2026 Hours: Monday through Friday 8:00-5:00 PM Onsite, in Menlo Park, CA Required Skills & Experience -Bachelor's degree or relevant coursework in engineering, research, or a related field (or equivalent experience). -Strong attention to detail and organizational skills. -Basic technical aptitude and familiarity with handling electronic devices. -Experience with FedEx shipping systems or package tracking preferred. - Basic knowledge of microsoft excel - Excellent communication and teamwork abilities. Job Description Overview: Insight Global is seeking a detail-oriented Research Assistant to support the deployment of prototype equipment for upcoming remote user studies. This role is part of a dynamic team responsible for testing and preparing electronic prototype devices before they are shipped to study participants. Key Responsibilities: - Assist in testing and validating prototype electronic devices to ensure full functionality prior to shipment. -Prepare, package, and ship devices to participants involved in remote, in-home studies using FedEx as the primary shipping method. -Track shipments and ensure timely delivery and return of study equipment. -Maintain detailed records of device testing, configurations, and shipping status. -Collaborate closely with research and engineering teams to ensure accuracy, quality, and timely deployment. -Troubleshoot and document any technical issues during pre-deployment testing. -Document in excel for additional tracking purposes Why Join Us: This is an exciting opportunity to contribute to cutting-edge research by ensuring the successful deployment of innovative technology.

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

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

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

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

⚡ 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: 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.

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

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

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

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

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.