Graduate research assistant jobs in Mountain View, CA

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

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

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

⚡ 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 ************************

SUPERCOMPUTING AI LAB W/ MULTIMODAL GENERAL AGENT AI STARTUP - SERIES A $1.2B VALUATION Goliath Partners has exclusively teamed up with an early stage startup AI Lab in SF currently valued at over $1B just after announcing their Series A. The firm has fundamental research bets on next-gen model architectures for long term memory and continual learning. Have lots of GPUs and are planning to get to frontier soon on the model side. Funding wise, their Series A was led by none other than Jann Tallinn. Jann has only led two other Series A's in the past - DeepMind and Anthropic! The team includes ex-DeepMind, Nvidia, Anthropic and Twitter professionals, and they are operating at the cutting edge of the AI space. They're hiring an ML Research Engineer to: Design and implement autonomous agents that can code, reason, and self-verify across real software environments Build full-stack infrastructure for prompt routing, task planning, retrieval, and sandboxed execution Apply post-training techniques (SFT, DPO, RLHF) and build eval benchmarks for multi-step reasoning and coding tasks Total Comp: $300-325k from a base perspective. Equity will also be involved at anywhere from .1% - 1% (equaling $1-10M in equity). If this sounds interesting, I'd love to share more. Please apply with an updated copy of your resume and Goliath will get in touch!

Role: Founding Applied Researcher Commitment: Full-Time, In Person Salary: up to $300k + 2% equity Must have previous AI/Multimodal/Generative systems experience About the Role Our client are building a fast-growing marketplace connecting elite creative talent award-winning artists, filmmakers, designers, and musicians with leading AI labs developing next-generation generative media models (e.g., state-of-the-art video, audio, and multimodal systems). A small, high-talent-density team with backgrounds from top universities and research-driven organizations, backed by founders and senior researchers from frontier AI labs and industry-leading research groups. They value initiative over instruction, autonomy over consensus, and reward exceptional talent with exceptional upside both in compensation and impact. Role Overview As a Founding Applied Researcher, you will design and build the next generation of generative media benchmarks evaluations that meaningfully push the boundaries of what foundation models can understand, generate, and perform. You will collaborate directly with researchers at frontier labs and fast-moving startups, helping define evaluation standards for multimodal and generative systems. This is a rare opportunity to own critical research efforts from day one, work on deeply novel challenges, and shape the direction of the field. What You'll Do Design, develop, and validate new benchmarks that test advanced real-world capabilities in generative media models Create novel evaluation methodologies, including dataset construction, task formulation, and scoring frameworks Collaborate closely with researchers at leading AI labs to identify gaps in existing evaluation pipelines and define new standards Prototype and iterate rapidly, balancing scientific rigor with practical constraints Influence research direction and help define best practices for a growing applied research organization What We're Looking For Academic & Research Background Master's degree or PhD in Machine Learning, NLP, Computer Science, or a related field Exceptional undergraduates with strong research track records are also encouraged to apply Demonstrated research excellence through publications at venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, or similar Technical Skills Strong proficiency in Python for research, prototyping, and experimentation Experience with evaluation, benchmarking, or model analysis Familiarity with multimodal systems, generative models, or foundation model behavior is a plus Mindset & Attributes Strong initiative and comfort operating autonomously Eagerness to tackle open-ended problems with no established playbook Ability to collaborate with industry researchers and clearly communicate findings Compensation & Ownership Competitive equity package with true founding-level ownership Opportunity to define foundational research culture and influence product direction from inception

, 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.

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 team The team is at the core of Li Auto's long-term vision to redefine intelligent mobility through Physical AI. As part of the Intelligent Driving division, we focus on two strategic pillars: Technical Foresight - Continuously tracking and decoding global innovations in embodied intelligence, world models, autonomous agents, and real-world foundation models. Frontier Research - Conducting exploratory studies and developing foundational capabilities that empower the next generation of autonomous systems. Our mission is to anticipate breakthroughs, translate them into actionable insights, and steer the organization's roadmap in AI planning, decision-making, and simulation. We closely monitor the progress of industry leaders like Tesla and Waymo, while also contributing to top-tier academic outputs. This is a team for researchers who think beyond today's limitations and are driven to architect the AI systems of tomorrow. Duties and responsibilities Strategic Leadership: Research and formulate the development of AI technology and business strategies, covering areas such as autonomous driving, embodied intelligence, physical AI, generative AI, etc. Drive cross-functional collaboration to identify emerging opportunities and define roadmaps for AI adoption and innovation. Technology Trend Analysis: Monitor global AI advancements, competitive landscapes, and regulatory changes (e.g., AI ethics, compliance frameworks) to inform strategic decision-making. Evaluate cutting-edge technologies (e.g., LLMs, reinforcement learning, multimodal AI) and assess their potential business impact. Ecosystem Development: Build partnerships with academia, industry consortia, and startups to foster co-innovation and leverage external expertise. Establish and maintain collaborative relationships with research institutions, industry associations, and other key stakeholders, and represent the company at conferences, technical committees, etc. Insight Delivery: Produce strategic and technical insight reports and presentations for executive leadership to inform global perspectives for business planning, and translate insights into strategic recommendations. Requirements Education/Experience Master's degree or higher in Artificial Intelligence, Robotics, Computer Science, Data Science, Electrical Engineering, or a related field. 3+ years of professional experience in autonomous driving and/or AI industries, with in-depth knowledge of technology trends, application scenarios, and technical foresight. Proven experience in technology foresight, strategy consulting, or academic research related to areas is highly preferred. Knowledge Familiar with technical architectures of autonomous driving and Physical AI systems, including planning, simulation, and LLM/VLM integration. Familiar with AI ethics, standards, and governance frameworks. Awareness of global industry and academic trends in intelligent mobility, robotics, etc. Skills and Competencies Strong analytical, synthesis, and strategic thinking capabilities to balance technical feasibility, market demands, and ROI. Exceptional communication skills to articulate complex AI concepts to non-technical stakeholders. Ability to work cross-functionally, manage uncertainty, and handle ambiguity in emerging technology domains. Bonus: Experience in AI-related product/technology R&D (e.g., AD/ADAS). Bonus: Proficiency in Chinese communication and writing for global collaboration. About Li Auto We're a leading Chinese new energy vehicle company that designs, develops, manufactures, and sells premium smart electric vehicles (EVs). Through product, technology, and business model innovations, we provide families with safer, more comfortable, and more convenient products and services.

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

⚡ 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 ************************

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

Role: Founding Applied Researcher Commitment: Full-Time, In Person Salary: up to $300k + 2% equity Must have previous AI/Multimodal/Generative systems experience About the Role Our client are building a fast-growing marketplace connecting elite creative talent award-winning artists, filmmakers, designers, and musicians with leading AI labs developing next-generation generative media models (e.g., state-of-the-art video, audio, and multimodal systems). A small, high-talent-density team with backgrounds from top universities and research-driven organizations, backed by founders and senior researchers from frontier AI labs and industry-leading research groups. They value initiative over instruction, autonomy over consensus, and reward exceptional talent with exceptional upside both in compensation and impact. Role Overview As a Founding Applied Researcher, you will design and build the next generation of generative media benchmarks evaluations that meaningfully push the boundaries of what foundation models can understand, generate, and perform. You will collaborate directly with researchers at frontier labs and fast-moving startups, helping define evaluation standards for multimodal and generative systems. This is a rare opportunity to own critical research efforts from day one, work on deeply novel challenges, and shape the direction of the field. What You'll Do Design, develop, and validate new benchmarks that test advanced real-world capabilities in generative media models Create novel evaluation methodologies, including dataset construction, task formulation, and scoring frameworks Collaborate closely with researchers at leading AI labs to identify gaps in existing evaluation pipelines and define new standards Prototype and iterate rapidly, balancing scientific rigor with practical constraints Influence research direction and help define best practices for a growing applied research organization What We're Looking For Academic & Research Background Master's degree or PhD in Machine Learning, NLP, Computer Science, or a related field Exceptional undergraduates with strong research track records are also encouraged to apply Demonstrated research excellence through publications at venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, or similar Technical Skills Strong proficiency in Python for research, prototyping, and experimentation Experience with evaluation, benchmarking, or model analysis Familiarity with multimodal systems, generative models, or foundation model behavior is a plus Mindset & Attributes Strong initiative and comfort operating autonomously Eagerness to tackle open-ended problems with no established playbook Ability to collaborate with industry researchers and clearly communicate findings Compensation & Ownership Competitive equity package with true founding-level ownership Opportunity to define foundational research culture and influence product direction from inception

SUPERCOMPUTING AI LAB W/ MULTIMODAL GENERAL AGENT AI STARTUP - SERIES A $1.2B VALUATION Goliath Partners has exclusively teamed up with an early stage startup AI Lab in SF currently valued at over $1B just after announcing their Series A. The firm has fundamental research bets on next-gen model architectures for long term memory and continual learning. Have lots of GPUs and are planning to get to frontier soon on the model side. Funding wise, their Series A was led by none other than Jann Tallinn. Jann has only led two other Series A's in the past - DeepMind and Anthropic! The team includes ex-DeepMind, Nvidia, Anthropic and Twitter professionals, and they are operating at the cutting edge of the AI space. They're hiring an ML Research Engineer to: Design and implement autonomous agents that can code, reason, and self-verify across real software environments Build full-stack infrastructure for prompt routing, task planning, retrieval, and sandboxed execution Apply post-training techniques (SFT, DPO, RLHF) and build eval benchmarks for multi-step reasoning and coding tasks Total Comp: $300-325k from a base perspective. Equity will also be involved at anywhere from .1% - 1% (equaling $1-10M in equity). If this sounds interesting, I'd love to share more. Please apply with an updated copy of your resume and Goliath will get 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.

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

⚡ 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 ************************

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

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.