Machine Learning Engineer Jobs in San Francisco

OpenAI

We are seeking a software engineer to build and evolve our classification and evaluation platform. You will develop services, online and offline pipelines, and tools that help researchers and data scientists turn an idea into a working measurement and iterate on it quickly. This role combines software and data engineering with hands-on production ownership. You will shape the architecture, deliver new capabilities, improve inference efficiency, and keep the system dependable as workloads and requirements evolve. Strong candidates will bring deep software engineering expertise and an interest in building a technical product in close partnership with its users.

$347k - $445k

Anthropic

The Account Abuse team is responsible for ensuring Anthropic's computing capacity is allocated fairly by minimizing resources for bad actors and preventing their return. As a software engineer on this team, you will build the machine learning systems that detect and stop abuse at scale. The ideal candidate can anticipate opponent strategies and responses to countermeasures. This role involves full-stack machine learning engineering across model training, productionization, and evaluation, with opportunities to leverage Claude to accelerate model development and maintenance. The focus is on classical ML applied to structured and behavioral data, emphasizing robust production systems, precise measurement, and safe rollout strategies, as false positives can lead to legitimate customer lockout.

$320k - $485k

Latent is seeking a Machine Learning Engineer, Research, to lead the design and development of innovative modeling approaches that push the boundaries of clinical intelligence. This role involves driving research from initial problem definition to validated outcomes, influencing how models learn from longitudinal patient data. We are looking for senior and staff-level engineers adept at managing critical research challenges from inception to completion, with a focus on problems that directly impact patient well-being.

$225k - $300k

Latent is seeking a Machine Learning Engineer to join their team and build systems that run in real clinical workflows. This role involves owning the design, development, and operation of production-grade ML systems from ambiguous problem definition through to reliable production deployment. The ideal candidate will drive systems end-to-end, setting technical direction and taking ownership of critical systems that directly impact real patient outcomes. This is an opportunity to work on mission-critical problems at the intersection of AI and healthcare within a fast-growing, early-stage company backed by top-tier investors.

$225k - $300k

Cerebras

The Core ML team is seeking an engineer to map novel algorithms for efficient large-scale AI training and inference to the Cerebras architecture. This role involves determining when these algorithms outperform competing approaches and how their advantages scale with models, workloads, and hardware. You will combine analytical performance modeling, empirical benchmarking, and hands-on prototyping to characterize the efficiency frontiers of emerging ML algorithms. Your work will span kernel-level and end-to-end performance, influencing research directions, implementation on current systems, and future hardware/software capabilities.

Salary not listed

Cerebras

The Core ML team is seeking an engineer to bridge the gap between novel machine learning research and efficient execution on Cerebras systems. You will work across ML frameworks, compilers, runtimes, and low-level kernels to implement new algorithmic capabilities, diagnose performance bottlenecks, and transform research prototypes into robust, high-performance demonstrations. Depending on your background, your work may emphasize runtime capabilities such as token orchestration, scheduling, communication, and distributed execution; low-level kernel development for novel ML operations; or a combination of both. This role is crucial for advancing the capabilities of Cerebras' unique AI chip architecture.

Salary not listed

Chai Discovery

Chai Discovery is building the computer-aided design suite for molecules, with major pharmaceutical companies already using their platform to accelerate drug discovery. They are at the forefront of reinventing life sciences through AI, developing frontier models that understand biochemical structure and interaction. This role is an opportunity to push the boundaries of AI drug design alongside a skilled and dedicated team.

Salary not listed

Typeface

We help the world's biggest brands move from brief to fully personalized campaigns in days, not months. Founded by Abhay Parasnis and backed by Microsoft, GV, Salesforce, Lightspeed, Madrona and Menlo, we’re building category-defining technology at the intersection of creativity and AI with real impact. Join us to help shape the future of enterprise marketing.

$188k - $200k

The Evaluation Foundations team is seeking a Senior Engineer to develop and improve high-performance tools for evaluating autonomous vehicle models. This role involves working across the technology stack to design, implement, and iterate on evaluation and introspection tools. You will contribute to a system that measures and visualizes AV model performance, helping to shorten the experimental path towards optimal models and enabling teams to understand model behavior more effectively. The work directly influences the safety, reliability, and scalability of next-generation autonomous systems.

$145k - $261k

Together AI

As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. You will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems, and contribute to the co-design of efficient GPU architectures and programming models. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. This internship is based on-site at our San Francisco HQ, running through the Winter term from January to April.

Salary not listed

NVIDIA's Silicon Co-Design Group (SCG) is seeking a Senior Memory Systems Engineer to lead the integration of HBM and LPDDR in sophisticated SoCs. This role spans the entire product development lifecycle, from architecture definition to silicon bringup and release, focusing on resolving complex system-level memory challenges. The engineer will be instrumental in ensuring memory subsystems meet performance, power, and reliability targets for next-generation products.

$196k - $311k

Our Mapping organization is building next-generation mapping systems that move beyond static HD maps toward automated, algorithmic, and ML-assisted map reconstruction pipelines powered by onboard sensor data. These systems form a critical foundation for localization, perception, simulation, and autonomy at scale. We are looking for a Senior Software Engineer to design and build the mapping algorithms and geospatial data systems behind automated map reconstruction and maintenance. In this role, you will develop the algorithms and data models that reconstruct, conflate, validate, and maintain map primitives from large-scale multi-modal sensor data, owning the geometric and topological correctness of the map itself. This is a hands-on individual contributor role with strong ownership, where you will drive technical problems end to end, partner closely with Perception, Localization, and Simulation, and apply machine learning where it measurably improves accuracy, coverage, or automation rate.

$171k - $261k

Together AI

As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. You will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems, and contribute to the co-design of efficient GPU architectures and programming models. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.

$121k - $146k

The Silicon Co-Design Group (SCG) is at the forefront of chip development, spanning architecture, design, marketing, operations, and productization across various markets including Datacenter, Gaming, Robotics, and Automotive. We are seeking a Senior Engineer to lead system validation, debug, and cross-functional alignment for critical silicon programs. This role is pivotal in ensuring product quality by identifying and resolving complex issues before they reach customers, and by building robust, AI-enabled validation capabilities. Your work will directly impact product success, escape rates, and customer confidence.

$168k - $311k

Together AI

The Model Shaping team at Together AI focuses on tailoring open foundation models for downstream applications, building services that help machine learning developers select and improve models with domain-specific data. We also develop novel methods for efficient model training and evaluation, drawing from machine learning, natural language processing, and ML systems. As a Research Engineer on the Scaling Team, you will translate cutting-edge research in efficient foundation model training into robust, high-performance systems. You will optimize Together's training infrastructure, identify performance bottlenecks, and implement state-of-the-art techniques in production environments. Your work will directly influence the fine-tuning experience for Together's customers. You will integrate newly released open-source models onto the platform, ensuring efficient and reliable training across diverse workloads. Collaborating with Research Scientists, you will build experimental infrastructure to accelerate research and deploy validated ideas at scale.

$200k - $290k

Together AI

The Model Shaping team at Together AI focuses on products and research for tailoring open foundation models to downstream applications. We build services that enable machine learning developers to select optimal models for their tasks and enhance them with domain-specific data. Additionally, we develop novel methods for efficient model training and evaluation, drawing from diverse ideas in machine learning, natural language processing, and ML systems. As a Platform Engineer in this team, you will operate at the intersection of backend engineering and infrastructure, developing the core layers of Together’s platform for model customization and evaluation. Your role will involve designing, developing, and maintaining the backend services and underlying systems necessary for sustainably and reliably scaling production workflows for users and internal research experiments. You will collaborate cross-functionally with other engineers and researchers to enhance infrastructure based on project needs and integrate services with other engineering teams at Together.

$200k - $290k

Together AI

Together AI is building the best inference infrastructure for voice applications, powering production-grade, real-time voice agents and applications with best-in-class latency and reliability for speech-to-text and text-to-speech models. We are seeking a Staff ML Engineer to lead the model serving layer for voice workloads. This role involves hands-on optimization of inference engines and models, profiling GPU utilization, designing batching strategies for streaming audio, and ensuring rapid deployment of new model architectures from research to production. This is a foundational hire on a small, high-impact team, addressing the unique challenges of voice inference such as streaming audio, tokenization, and real-time latency budgets, and shaping the future of voice model serving.

$220k - $280k

Together AI

Together AI is building the best inference infrastructure for voice applications, powering real-time voice agents and applications with best-in-class latency and reliability for speech-to-text and text-to-speech models. We are seeking a Senior ML Engineer to lead the model serving layer for voice workloads. You will optimize inference engines like TRT-LLM and SGLang to serve models such as Whisper, Parakeet, Orpheus, and Kokoro, focusing on pushing latency and throughput boundaries. This role involves profiling GPU utilization, designing batching strategies for streaming audio, and accelerating the transition of new model architectures from research to production. As a foundational hire on a small, high-impact team, you will address the unique challenges of voice inference, including streaming audio, real-time latency, and tokenization, shaping how Together serves voice models as the industry moves towards end-to-end speech-to-speech systems.

$200k - $260k

Together AI

Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models and ensuring they run efficiently and effectively at scale. You will have the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions and shape the future of AI inference.

$200k - $300k

Handshake is seeking a Member of Technical Staff, Post-Training to help define and build a new organization focused on advancing the AI economy by organizing expert human knowledge. This role involves working directly with frontier labs on data, evaluation, and post-training challenges, building systems that transform expert knowledge into data and evaluations to improve frontier models. You will partner with researchers, domain experts, and customers to translate ambiguous post-training questions into experiments, evaluation frameworks, data pipelines, and products. As an early member, you will have significant influence over the technical direction, operating culture, and reusable systems built.

$200k - $350k

OpenAI

The Monetization team is a new cross-functional group focused on building foundational systems to responsibly scale access to intelligence. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences, that strengthen user trust, unlock economic opportunity, and support OpenAI's long-term innovation. This role operates in a greenfield environment, moving quickly through prototyping, experimentation, and iterative deployment, partnering closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. As a Research Engineer, you will contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions and making AI technology accessible and impactful.

$381k - $555k

Applied Intuition

The Axion Data team at Applied Intuition is building the data engine to train perception models. This role involves working on both the edge application that runs perception stacks and the cloud data engine that ingests video data for model improvement. The goal is to optimize model performance on edge and cloud, and build MLOps tooling for pipeline visibility. This position offers an opportunity to own and impact a new product team within a rapidly growing company.

$200k - $275k

Databricks

Databricks is seeking a Staff Engineer to join the Customer Engagement and Docs platform team, focusing on enhancing customer support through AI and Large Language Models (LLMs). This role operates at the intersection of Product development and Machine Learning, aiming to help customers resolve issues faster by providing precise solutions or facilitating seamless escalations. You will gain a deep understanding of user behavior, identify problem drivers, and leverage ML and LLMs to analyze complex technical use cases within an enterprise environment, ultimately guiding them towards resolution.

$190k - $260k

Applied Intuition

Applied Intuition is seeking a Software Engineer to join their team and contribute to powering the future of physical AI. This role involves constructing optimized data pipelines for ML models and evolving the data engine architecture to scale high-fidelity labels, reduce annotation costs, and accelerate ML iteration cycles. You will also integrate foundation models like LLMs and VLMs to automate and enhance labeling, quality assurance, and data discovery, while leveraging software-in-the-loop and hardware-in-the-loop testing. Additionally, you will interact with customers to understand their use cases and triage needs during field events.

$200k - $275k