AI Research Engineer Jobs in San Francisco

Anthropic

Anthropic is dedicated to building reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. This role focuses on Multi-Agent systems, which are increasingly vital for AI deployment, from small subagents within products to large groups tackling complex problems. Training Claude for optimal performance and safety in these large groups is a challenging new frontier in reinforcement learning and a new way to scale compute at test time.

$500k - $850k

Assort Health

Assort Health is building a continuous conversation for every patient, powered by an AI agent that remembers context and carries it through their healthcare journey. The company has developed a proprietary dataset of 285 million patient interactions and is experiencing rapid growth, having raised $222 million. As a Research Engineer, you will be responsible for developing industry-leading healthcare AI models and pipelines, taking them from concept to production. You will own significant initiatives to advance the capabilities of AI models and agents in healthcare, ensuring high levels of reliability, efficiency, and precision.

$190k - $240k

Together AI

As a Research Intern in the Model Shaping team, you will contribute to advanced post-training methods, explore new techniques for efficient neural network training, and work on robust evaluation of foundation model capabilities. The Model Shaping team focuses on tailoring open foundation models for downstream applications, developing services for model selection and improvement, and creating new methods for efficient model training and evaluation. This role offers the opportunity to work on cutting-edge research, potentially leading to publications in top-tier conferences.

$58k - $70k

Together AI

As a Research Intern in the Model Shaping team, you will contribute to advanced post-training methods, explore new techniques for efficient neural network training, and work on robust evaluation of foundation model capabilities. The Model Shaping team focuses on tailoring open foundation models for downstream applications, developing services for model selection and improvement, and creating new methods for efficient model training and evaluation. This role offers the opportunity to work on cutting-edge research, potentially leading to publications in top-tier conferences.

$58k - $70k

Together AI

The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, advancing open and transparent AI. This role operates at the intersection of model architectures, high-performance systems engineering, and hardware optimization, focusing on co-designing software, algorithms, and models to reduce the cost and latency of AI systems. As a research intern, you will explore distributed inference, compiler-aware optimization, and novel inference-time computation strategies, co-designing and implementing cross-layer optimizations across models, systems, and hardware, with a focus on KV cache design and large-scale serving architectures. Projects aim to unlock unprecedented performance and scale for foundation models, enabling faster serving, larger model deployment, and robust evaluation under realistic serving workloads.

Salary not listed

Together AI

The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, advancing open and transparent AI. This role operates at the intersection of model architectures, high-performance systems engineering, and hardware optimization, focusing on co-designing software, algorithms, and models to reduce the cost and latency of AI systems. As a research intern, you will explore distributed inference, compiler-aware optimization, and novel inference-time computation strategies, co-designing and implementing cross-layer optimizations across models, systems, and hardware.

Salary not listed

Together AI

The Agents team focuses on building, aligning, and scaling advanced AI systems capable of handling complex, multi-step tasks and workflows across text and speech, particularly in agentic and scientific domains. This role sits at the intersection of agent capabilities, human-computer interaction, and infrastructure, exploring areas like post-training methods for agentic behavior and evaluation frameworks for open-ended tasks. As a research intern, you will contribute to cutting-edge agentic AI challenges, addressing issues of alignment, reliability, and scalability. Projects may involve developing new training techniques for self-learning and long-horizon reasoning, curating datasets for scientific and agentic tasks, analyzing agentic behavior failure modes, or building scalable agent operation infrastructure.

Salary not listed

Together AI

The Agents team investigates how to build, align, and scale frontier AI systems capable of complex, multi-step tasks across text and speech, focusing on agentic and scientific domains. This role sits at the intersection of agent capabilities, human-computer interaction, and infrastructure, exploring areas like post-training methods for agentic behavior and evaluation frameworks for open-ended tasks. As a research intern, you will tackle challenges in alignment, reliability, and scalability, potentially working on new training recipes for self-learning, curating datasets for non-deterministic tasks, studying agentic behavior failure modes, or building large-scale agent operation infrastructure.

Salary not listed

Together AI

Together AI's Model Shaping team focuses on tailoring open foundation models for downstream applications, building services that help ML developers select and improve models with domain-specific data. The team also develops efficient model training and evaluation methods, drawing from machine learning, NLP, and ML systems. As a Research Engineer, you will develop a platform for users to customize open-source models with their own data, working across training and inference stacks. You will build and enhance services for Fine-Tuning, Reinforcement Learning, and Evaluation, ensuring a smooth transition from post-training to production serving and optimizing inference engines for RL training. Collaboration with product, research, and engineering teams is key to maintaining API reliability and performance, ultimately contributing to the foundational layer of the open-source AI ecosystem.

$200k - $290k

WRITER is a company focused on orchestrating AI-powered work for leading enterprises, aiming to expand human capacity through superintelligence. Their platform enables companies to build and deploy AI agents grounded in their data and powered by enterprise-grade LLMs. WRITER is a rapidly growing company in the enterprise generative AI space, seeking talented individuals to join their mission to create a better future of work with AI.

$199k - $325k

Roboflow

Roboflow Labs is seeking a Research Scientist to join their applied research unit. This role sits at the intersection of benchmarks, models, and frontier labs, focusing on failure analysis, dataset specification, and validation of data quality. The scientist will contribute to publishing new benchmarks, extending existing ones like RF100-VL, and shaping the research agenda with work grounded in real-world deployments. This position offers the opportunity to see research directly translate into shipped data products and influence the direction of AI development.

$250k - $450k

Thinking Machines Lab

Thinking Machines is building AI that extends human will and judgment, focusing on training frontier models, developing tools for model customization, and crafting interfaces for human-AI communication. This role is crucial for shaping the fundamental reasoning capabilities of our models by owning the late-stage training process. It involves a blend of fundamental research and practical engineering, making it ideal for individuals comfortable working at the intersection of pre-training and post-training.

$350k - $475k

Databricks

Databricks AI Research is seeking a Principal Research Scientist – Scaling to lead a team focused on advancing the state of the art in large-scale machine learning, particularly in LLM training and inference efficiency. This role involves defining and executing a research roadmap to improve how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders. The goal is to push the boundaries of LLM efficiency beyond existing models, exploring novel algorithms, systems, and infrastructure improvements. You will drive independent research agendas and collaborate on low-level implementation details to bring cutting-edge methods into production and enhance the Databricks AI platform.

$280k - $350k

Databricks

Databricks AI is seeking a Principal AI Research Scientist to lead a team focused on advancing the state of the art in large-scale machine learning, particularly in LLM training and inference efficiency. This role involves defining and executing a research roadmap to improve how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders. The ideal candidate will drive algorithmic innovations, optimize ML systems for distributed training and inference, and translate research breakthroughs into customer-impacting capabilities within the Databricks AI platform. This position also requires fostering a culture of scientific excellence, representing Databricks AI externally, and mentoring research talent.

$270k - $340k

As a Research Scientist at Mercor, you will work at the intersection of research and engineering on frontier post-training. You will develop new training and evaluation methods, test them through rigorous experiments, and implement successful approaches at scale. Working with researchers, engineers, domain experts, and customers, you will investigate how data, rewards, environments, and optimization methods shape model behavior. Your work will influence frontier models, Mercor’s products, and the broader research community through releasing blogposts, technical reports, and papers.

$250k - $500k

Thinking Machines Lab

At Thinking Machines, we build tools that empower individuals to customize AI models for their specific needs, including the ability to train model weights. In this role, you will focus on frontier customization techniques and contribute to developing a leading post-training engine called Tinker. Your work will involve a comprehensive understanding of Reinforcement Learning (RL) science, and your findings will directly influence Tinker's training defaults, API design, and the open-source Tinker Cookbook. You will collaborate with internal research teams and contribute to open science initiatives for external partners.

$350k - $475k

Thinking Machines Lab

Thinking Machines is building AI that extends human will and judgment, with a focus on training frontier models and developing tools that allow users to customize AI for their unique needs. This role leads the Fine-tuning Science team, focusing on frontier customization techniques and the Tinker post-training engine. It's a player-coach position where you will remain hands-on with scientific research while also guiding the team, shaping its direction, and ensuring research findings are integrated into Tinker. You will collaborate with internal research teams, contribute to open science, and engage with external users.

$350k - $475k

Cursor

As a Research Engineer on the Synth Data team at SpaceXAI, you will invent and scale the synthetic data that teaches our models new capabilities. You will own the full loop: spotting a capability the model is missing, designing a data generation strategy, building reliable pipelines and verifiers, and validating that the resulting data actually moves the model. You will form hypotheses about what data will help, build the systems to produce it at scale, run ablations, and read the resulting traces and training signals to understand why it worked (or didn’t). Your datasets will go directly into frontier training runs and shape the development of Grok models.

Salary not listed

Genmo is a research lab focused on developing advanced video world models to understand, simulate, and interact with the physical world, aiming to advance physical intelligence and enable robots to learn and act. We are seeking an exceptional Software Engineer to join our research team in pushing the boundaries of visual generative AI. In this role, you will collaborate with experienced researchers to develop and enhance generative models, ensuring their safe and effective deployment. This is an opportunity to contribute to cutting-edge AI research in a fast-paced startup environment.

Salary not listed

AfterQuery

AfterQuery is an applied research lab focused on curating data solutions for foundation model development, serving frontier AI labs with the mission of making expertise widely accessible. This is a unique opportunity to join a rapidly growing company at a pivotal moment in AI. We are backed by leading investors and have a strong founding team with experience from top tech and finance companies. We are seeking exceptional undergraduate and masters students for our AI/ML Research Internship program to work on cutting-edge AI projects in advanced reasoning, computer use, and agentic models. Interns will have access to expert networks and specialized datasets, with opportunities to co-author research papers and present at leading AI conferences.

Salary not listed

OpenAI

We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis, building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists.

$380k - $500k

Abundant

Abundant is building the NVIDIA of training data, recognizing the critical need for scaling data as AI models advance beyond supervised learning to reinforcement learning and learning from experience. The founding team brings extensive experience from leading AI organizations, with a proven track record in deploying deep learning models at scale, training state-of-the-art models, and managing large data pipelines. As a Member of Technical Staff, you will collaborate directly with the founding team to architect the future of model reasoning and intelligence, working at the intersection of research and execution to push the boundaries of AI capabilities.

$120k - $120k

FAR.AI, a non-profit AI research institute dedicated to ensuring advanced AI is safe and beneficial, is seeking a Research Lead to spearhead its pre-training safety initiatives. This role focuses on shaping AI models at their source by controlling capabilities and internal representations, aiming to prevent misuse and reduce loss-of-control risks. The work involves scaling methods for large models, validating approaches like data filtering and gradient routing, and exploring techniques such as unlearning. The Research Lead will direct these efforts, collaborate with red teams for stress-testing, and analyze scalability to frontier systems. This position offers significant autonomy within an impact-driven environment, focusing on empirically grounded, scalable ML safety research.

$290k - $450k

NVIDIA AI for Media is seeking outstanding engineers to join its team, focusing on building and optimizing real-time AI solutions for media and entertainment workflows. This role will involve setting the technical direction for content authenticity AI, architecting model and pipeline strategies for detecting synthetic and manipulated media, and making critical build-vs-adapt decisions. The team works on core technologies to solve ambitious computer vision and deep learning problems, aiming to deliver studio-quality audio and high-resolution video enhancement and effects.

$272k - $431k