AI Engineering Jobs in San Francisco

Scale AI

Scale AI is seeking a Frontier Agent Engineer (Forward Deployed Engineering) to work directly with strategic enterprise customers. In this role, you will architect, integrate, deploy, and operate production AI systems, combining modern software engineering, distributed systems, cloud infrastructure, and frontier AI technologies. You will design production agent architectures, integrate with customer systems, deploy AI into mission-critical workflows, and help shape best practices for enterprise AI. This role is ideal for individuals who enjoy solving complex systems problems, rapidly prototyping AI capabilities, and bringing frontier AI into production.

$180k - $225k

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 AI is seeking a Senior/Staff Machine Learning Engineer to join the General Agents team, focusing on building robust, production-ready AI agents for enterprise use cases. This role involves working across the entire agent lifecycle, from design and development to evaluation, deployment, and iteration. You will translate cutting-edge agentic techniques into reliable systems that solve high-impact business problems, emphasizing generalization, extensibility, and deployment across multiple customers. The team operates at the intersection of frontier agent development and real-world application, aiming to deliver significant economic value through scalable agent systems.

$290k - $363k

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 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 fundamental challenges 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 role involves collaborating broadly across industry, the public sector, and academia, and regularly publishing findings to shape the future of AI safety and alignment.

$216k - $270k

Scale AI

Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs, as well as data quality evaluation. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development, enabling the next generation of LLM training, inference, and data curation.

$190k - $237k

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

Databricks

Databricks is seeking a Senior Software Engineer for its AI Runtime (AIR) team. AIR is a managed platform designed for large-scale GPU training and fine-tuning of AI models, providing customers with on-demand access to accelerators and a serverless experience that simplifies the complexities of provisioning, scheduling, and orchestrating multi-node jobs. As a Senior Software Engineer on AIR, you will be instrumental in building and scaling the systems that ensure large-scale training is fast, reliable, and effortless. You will lead the architecture and evolution of the managed GPU training stack, focusing on areas such as scheduling, distributed training performance, fault tolerance, and the developer experience for large-scale job operations. Beyond hands-on system development, you will contribute to the technical vision for AIR, mentor engineers, and collaborate with product, research, and platform teams to expand the impact of custom AI training at Databricks.

$160k - $225k

OpenAI

We are seeking a Researcher to lead our safety and alignment research, focusing on building systems that can distinguish valuable web content from spam, manipulation, and other adversarial or low-quality material. This role involves tackling the challenge of detecting coordinated manipulation that may not be apparent when evaluating individual pages in isolation. As AI advances the ease of producing convincing content at scale, you will be responsible for adapting detection systems to counter increasingly sophisticated adversaries. You will define the technical strategy, develop classifiers and evaluations, and influence how integrity signals shape Search's indexing and retrieval processes. Collaborating closely with Search and broader Safety and Integrity teams, you will leverage frontier models to enhance detection methods and implement them in production.

$380k - $850k

Relace

Relace is building a globally distributed inference cloud, competing on price, speed, and reliability. We process over 800 billion tokens daily and have experienced significant growth, backed by a $23 million Series A funding round. Our team is small, offering substantial responsibility and growth opportunities. We develop our own stack, running on Kubernetes across multiple clouds, where performance directly impacts business success. This role focuses on the lowest level of our stack, optimizing code that runs directly on GPUs to maximize work per second and dollar, shrink models for cost-efficiency without sacrificing quality, and eliminate GPU idle time.

Salary not listed

Wayve is building the AI platform for autonomous driving, enabling vehicles to learn directly from real-world experience and adapt at scale. This role is on the Vehicle Generalization Team, focused on making Wayve's core autonomy generalize across a wide range of vehicle platforms. You will work on pre- and post-training methods to improve AI model generalization, specifically addressing how models perform with changes in perception and embodiment across different vehicles. Your work will directly impact production programs with major OEMs.

$370k - $420k

Lila Sciences is developing the infrastructure for autonomous science, creating AI systems that can design and execute experiments in physical labs across life sciences, chemistry, and materials science. Their platform is designed for reliability and scale, catering to external customers who demand security, auditability, and operational rigor. This role focuses on building foundational enterprise systems to support large pharmaceutical and research organizations, enhancing capabilities like multi-tenancy, identity management, granular permissions, audit infrastructure, and billing. The position involves pushing the boundaries with agentic AI-powered systems for self-service tenant management, intelligent customer observability, and automated compliance workflows, alongside developing an AI-native external API.

$192k - $288k

SambaNova

SambaNova is seeking an Inference Systems Performance Architect to lead the end-to-end performance strategy for their AI inference platform. This role involves defining and driving technical direction in workload capture, benchmarking, modeling, and simulation. You will be instrumental in understanding how requests move through the system, from tokenization to fabric communication, and how deployments meet customer service level objectives. The work focuses on creating reproducible representations of real and agentic traffic, developing what-if capabilities for future configurations, and tackling complex challenges in heterogeneous inference environments.

$245k - $325k

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

Reflection ai

Reflection's Data team is responsible for building the training corpora that our frontier models learn from. The ingestion layer is the critical machinery that transforms raw data from the open web, licensed sources, and other large-scale origins into well-structured, versioned, and auditable datasets for pre-training. As the Data Ingestion Lead, you will provide front-line leadership for the team responsible for this layer, overseeing web crawl, data ingestion pipelines, and data lakes. You will build, mentor, and grow a team of data ingestion engineers, guide technical and architectural decisions across crawling, extraction, and corpus storage/delivery, and collaborate closely with research, data quality, and data partnerships teams. You will also remain hands-on to contribute technically and maintain a deep understanding of the team's work, as subtle decisions at the ingestion layer significantly impact model performance, safety, and failure points.

Salary not listed

Imbue is an AI company building a suite of open-source tools to make technology serve humans. We are creating a future where individuals own personal teams of AI agents that can be modified to their specific needs. Our projects include Studio, a custom digital HQ for building personalized software; Bouncer, a social media feed filter; and Sculptor, an interface for programmers to run coding agents in parallel. We are seeking a Product Engineer to shape our product and build 0-1 features, contributing to the overall product direction. This role involves building across the entire stack, understanding customer needs, and contributing to the product roadmap, making it ideal for individuals with founder aspirations.

$170k - $350k

Cargo

Plaid is seeking a Staff Machine Learning Engineer to join the Data Foundation & AI team. This team builds the shared ML and AI infrastructure that powers intelligent capabilities across Plaid's product suite, transforming unique financial network data into scalable, general-purpose representations. The role involves working at the intersection of machine learning infrastructure, applied AI, and distributed systems to establish the core AI platform that enables innovation. The Staff ML Engineer will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches. This position requires establishing rigorous evaluation frameworks, building scalable pipelines, and partnering with teams across the organization to define product integrations with foundation models. As a senior technical leader, you will mentor engineers, elevate engineering standards, and represent Plaid's AI and machine learning capabilities externally.

$249k - $368k

Ema builds AI Employees for HR, IT, and Finance, automating busy work across the employee experience. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team comprises engineers from premier tech companies and graduates of top universities. We are backed by leading investors and are at the forefront of Agentic AI, shipping real systems that run business processes at scale. We are seeking innovative and passionate Machine Learning Engineers who excel at solving complex problems with large datasets, transforming theoretical concepts into practical, scalable solutions, and pushing the boundaries of Natural Language Processing and Information Retrieval.

$160k - $220k

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

We are seeking a mathematically rigorous engineer to own model numerics, focusing on how we measure, bound, and reason about the numerical behavior of models and how this analysis informs deployment decisions. The core challenge involves determining if numerical differences between model versions are safe, connecting low-level concepts like floating-point drift to high-level outcomes like vehicle trajectory error. You will build the tooling to quantify these connections and define the thresholds for ship/no-ship decisions. This role requires more than just running existing validation; it demands the ability to investigate and explain the root causes of numerical divergence.

$171k - $261k

Capital One is building responsible and reliable AI systems to transform banking. Leveraging deep experience in machine learning and investments in technology, the company aims to be at the forefront of enterprise AI adoption. This role is within the Intelligent Foundations and Experiences (IFX) team, which is central to realizing Capital One's AI vision. The team builds and deploys proprietary AI solutions that deliver value to millions of customers and empower other teams across the company to enhance their products with AI in responsible and scalable ways.

$197k - $225k

Databricks

Databricks is seeking a Staff Software Engineer for its AI Runtime (AIR) team. AIR is a managed platform designed for large-scale GPU training and fine-tuning of state-of-the-art AI models, providing customers with on-demand access to accelerators and a serverless experience. As part of this role, you will be instrumental in building and scaling the systems that ensure fast, reliable, and effortless large-scale training. You will influence the architecture and development of the managed GPU training stack, focusing on areas like scheduling, distributed training performance, fault tolerance, and the overall developer experience for operating jobs at scale. This position also involves defining the long-term technical vision for AIR, mentoring senior engineers, and collaborating with product, research, and platform teams to expand the impact of custom training at Databricks.

$190k - $265k

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