AI Research Engineer Jobs in San Francisco

Outset is building AI systems, referred to as digital twins, that represent specific real people and can respond to research questions as those individuals would. These systems are used by global brands to gain deeper qualitative insights about their users at unprecedented speed and scale. The Digital Twins Team focuses on measuring and improving the faithfulness of these AI systems in reproducing human responses and behavior. The Research Scientist will work closely with the Head Scientist to define research questions, design studies, establish measurement criteria, interpret findings, and contribute to internal decision-making and potential academic publications. This role requires a strong background in computational social science, data science, survey methodology, human-computation interaction, and experiment design.

$200k - $240k

Reflection ai

Reflection is a research lab dedicated to making intelligence open and accessible for everyone. We build open models that empower individuals to control their intelligence and shape the future of AI. This role focuses on the foundational aspects of AI development, specifically in pre-training data, contributing to the creation of open foundational models. You will be part of a talented team, helping to define the company's future and the future of open AI.

Salary not listed

Scale AI

Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. As AI rapidly evolves from static models to dynamic, agentic systems, Scale is building the foundational research, evaluation methodologies, and agent/RL infrastructure that will define this next era. You’ll join a high-impact research organization driving advances in large-language models, post-training, evaluation, and agentic/RL environments, helping shape how next-generation AI is built, measured, and deployed.

$290k - $363k

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. Our founding team brings deep expertise from leading AI organizations, with a proven track record in deploying large-scale deep learning models, training state-of-the-art self-driving models, and managing massive data pipelines. We are at the forefront of innovation, addressing the scarcity of training data by advancing simulation, synthetic data generation, and learning from experience, which are essential for achieving AGI, ASI, and physical intelligence. We partner with top AI labs and enterprises to provide the data necessary for models to move from general knowledge to domain expertise and from chatbots to agents.

$168k - $168k

Outset is building AI-powered user interviews, creating digital twins that represent specific real people and respond to research questions as those individuals would. The Digital Twins Team focuses on measuring and improving how faithfully these AI systems reproduce human responses and behavior. As a Research Engineer, you will report to the Head Scientist and be responsible for building and maintaining the systems that enable the team's scientists to conduct their studies correctly, reproducibly, and at scale. Your role involves ensuring experiments execute as designed, results are reproducible, and research code stays aligned with the shipped product, supporting scientists in a computational research setting with hands-on experience in LLM-based systems.

$200k - $240k

Scale AI

This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

$302k - $378k

Scale AI

Scale Labs is seeking a Research Scientist focused on Safety Post-Training to develop and apply methods for making frontier AI systems safer and more understandable. This role involves designing and executing post-training pipelines to analyze how training choices impact model safety, robustness, and alignment. You will also develop evaluations informed by interpretability techniques to uncover the reasons behind undesirable model behaviors and use these insights to guide targeted safety mitigations. A key aspect of this position is collaborating with policymakers, engineers, and other researchers to translate findings into actionable safety standards, benchmarks, and best practices.

$216k - $270k

Scale AI

Scale Labs is launching a new team focused on policy research to bridge the gap between AI research and global policymakers, enabling informed, scientific decisions about AI risks and capabilities. This team tackles complex problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. The Research Scientist, AI Controls and Monitoring will design methods, systems, and experiments to ensure advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments.

$216k - $270k

Scale AI

Scale works with leading AI labs to accelerate GenAI research by providing high-quality data. This role focuses on optimizing data curation and evaluation to enhance LLM capabilities in text and multimodal modalities. You will develop novel methods to improve the alignment and generalization of large-scale generative models, collaborate with researchers and engineers on best practices in data-driven AI development, and partner with foundation model labs to provide technical and strategic input on next-generation generative AI models.

$166k - $207k

OpenAI

The Foundations Research team is focused on high-impact, forward-looking AI research, particularly for future frontier models. Within this team, the Search group is developing agentic search capabilities by co-designing model-system interfaces with the core search stack, including serving, indexing, and retrieval. We build and research large-scale systems to transform and index vast amounts of data, enabling AI models to effectively find and reason over information. This role involves researching and developing methods for extracting and utilizing semi-structured knowledge graphs from heterogeneous web content. The core objective is to make this information more accessible and useful for AI models, addressing key questions about the optimal structure for information retrieval, scalable extraction techniques, and how to measure and improve model reasoning capabilities. You will collaborate across research, data, and systems to advance how knowledge is extracted, organized, and retrieved, with potential for scientific publication and impact across OpenAI products.

$380k - $850k

Anthropic

Anthropic is seeking a Research Engineer for its Code RL team, focused on advancing AI models for silicon design. This role involves leveraging chip design expertise to create tasks and signals for AI models, aiming to improve their capabilities in areas like RTL generation, design verification, and physical design optimization. The position sits at the intersection of cutting-edge research and engineering, with a commitment to building high-quality, scalable AI systems.

$500k - $850k

Etched is building AI systems that accelerate its own development. As a Research Engineer on the RL Frontiers team, you will train proprietary frontier models to automate kernel development, ASIC engineering, production pipelines, and 3-D hardware operating systems. You will use proprietary simulators and environments to create custom data mixes and post-train models to SOTA performance on the company's hardest engineering tasks. The company is focused on inference and bets on transformer architectures, aiming to capture the entire inference market. Etched is a fully in-person team in San Jose, valuing engineering skills and expecting technical staff to contribute to both engineering and research across disciplines.

From $400k

Anthropic

Reinforcement learning is crucial for training AI models like Claude to reason, write code, and act autonomously. At scale, RL training involves complex distributed systems running across numerous accelerators and hosts. As an engineer in RL Engineering, you will be responsible for securing this expanding system. This is a hands-on role where you will work directly within the RL codebase and its underlying infrastructure, collaborating with the engineers and researchers who develop and utilize it. The system's rapid evolution, driven by research advancements, requires security solutions that maintain pace without compromising performance or development velocity. We are seeking candidates with expertise in either security engineering for large-scale ML systems or ML systems/research engineering with a strong interest in security.

$320k - $405k

Sygaldry Technologies

Sygaldry Technologies is developing quantum-accelerated AI servers to dramatically speed up AI training and inference. By merging quantum computing with AI, the company aims to accelerate the development of superintelligence and ensure its efficient and affordable operation. Their unique approach involves integrating multiple qubit types into a single, fault-tolerant architecture to achieve the necessary cost, scale, and speed for advanced AI applications. Sygaldry is at the forefront of new discoveries in physics, engineering, and AI, tackling complex challenges with a grounded, optimistic, and rigorous culture. They are seeking individuals passionate about defining the future at the intersection of quantum and AI and driving its global impact.

$125k - $145k

Salesforce AI Research is seeking entrepreneurial Research Interns for Summer 2027 to help build the next generation of Enterprise AI. This is a unique opportunity to work like a founder within Salesforce, exploring high-impact research directions, prototyping cutting-edge AI capabilities, and seeing how ideas are validated with customers and turned into production-ready solutions. Interns will have the freedom to propose and explore new ideas alongside mentors and research scientists, with access to Salesforce's global customer and product ecosystem. The role is ideal for individuals comfortable with ambiguity, bringing energy and focus, and who care as much about customer adoption as technical innovation, offering the pace and ownership of a startup with the reach and resources of Salesforce.

Salary not listed

Anthropic

The Cybersecurity RL team within Horizons is seeking a Research Engineer to advance the capabilities of AI models in secure coding, vulnerability remediation, and defensive cybersecurity. This role combines research and engineering, involving the design and implementation of RL environments, conducting experiments, delivering work into production training runs, and collaborating with cross-functional teams. The ideal candidate will possess domain expertise in cybersecurity and an interest in training safe AI models, potentially coming from backgrounds such as white hat hacking, security engineering, or detection and response.

$500k - $850k

Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The Interpretability team focuses on mechanistic interpretability, aiming to discover how neural network parameters map to meaningful algorithms. This involves reverse-engineering how trained models work, treating neural networks like biological systems or computer programs to be reverse-engineered. The team's goal is to create a solid scientific foundation for understanding neural networks and making them safe, with a focus on issues like "superposition" and decomposing models into interpretable components. This role supports a team of expert researchers and engineers working on these ambitious safety research goals.

$350k - $500k

Anthropic

The Interpretability team at Anthropic is dedicated to reverse-engineering how trained models work, believing that a mechanistic understanding is crucial for making advanced AI systems safe and steerable. This role focuses on mechanistic interpretability, aiming to discover how neural network parameters map to meaningful algorithms, akin to performing "biology" or "neuroscience" on neural networks. The team has made significant progress in understanding issues like "superposition" and decomposing models into interpretable components, with recent work identifying millions of features in production models and developing methods to understand multi-hop reasoning and planning. This research is foundational for building reliable, interpretable, and steerable AI systems and often involves collaboration with other teams at Anthropic to enhance AI safety.

$350k - $850k

Thinking Machines Lab

Thinking Machines is building AI that extends human will and judgment. We are developing Tinker, a fine-tuning API that empowers researchers and developers to customize frontier AI models. This role focuses on building and enhancing our training systems for Tinker, specifically involving RL systems, numerics, and kernels, to enable users to train models with their own data and algorithms.

$350k - $475k

Genmo is a research lab developing sophisticated video world models to understand, simulate, and interact with the physical world, aiming to unlock the right brain of AGI. We are seeking an exceptional Research Scientist to focus on alignment and post-training techniques for large-scale video generation models. This role is at the forefront of ensuring our diffusion-based video models reliably produce high-quality, physically accurate, and safe outputs that align with human preferences and values.

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 unlock the right brain of AGI. We are seeking an exceptional Research Scientist to pioneer cutting-edge diffusion models for text-to-video generation. This role involves creating novel architectures and algorithms to transform written descriptions into high-quality, coherent video content, pushing the boundaries of physical intelligence and enabling robots to learn and act in dynamic environments.

Salary not listed

Together AI

The Speculative Decoding team at Together AI focuses on developing draft models and algorithms to accelerate large language model generation without altering outputs. Their work integrates model training, inference algorithms, and serving systems, optimizing all three for reduced cost and latency. As a research intern, you will explore open questions in speculative decoding, including new drafter architectures, verification schemes, knowledge distillation, and adaptive drafters. You will train and fine-tune draft models at scale on GPU clusters and evaluate your solutions against realistic serving workloads, such as long-context and agentic traffic.

Salary not listed

Prime Intellect

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training for post-training at frontier scale. They are developing open-source models for long-horizon tasks and the platform their research team uses. The company has raised $150M from prominent investors and AI leaders. They are seeking individuals passionate about building at the intersection of frontier research, infrastructure, and go-to-market strategy for a nascent category. This role focuses on building the data foundation for Prime Intellect's next generation of open models. You will identify and process valuable data sources, transforming them into training-ready corpora. Your work will directly influence both broad pretraining efforts and the development of specific capabilities like reasoning, coding, and long-context learning. You will collaborate closely with researchers to test and refine data strategies, ensuring the data effectively improves model performance.

$150k - $350k

Together AI

The Speculative Decoding team at Together AI focuses on developing draft models and algorithms to accelerate large language model generation without altering outputs. Our work spans model training, inference algorithms, and serving systems, aiming to reduce generation cost and latency. As a research intern, you will explore open questions in speculative decoding, including new drafter architectures, verification schemes, knowledge distillation, and adaptive drafters. You will train and fine-tune draft models at scale on GPU clusters and evaluate your ideas against realistic serving workloads, such as long-context and agentic traffic. Projects are designed to address key research questions in speculative decoding, leading to faster generation on frontier models, drafters that adapt to changing workloads, and robust evaluation under real traffic.

Salary not listed