Machine Learning Engineer Jobs in San Francisco

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.

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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.

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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.

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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

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.

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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

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

Databricks

The Applied AI team at Databricks is at the forefront of advancing GenAI-powered products, having launched Databricks Assistant, AI/BI Genie, and Agent Bricks. These products are used by hundreds of thousands of users daily, tackling challenging problems like code suggestion, text-to-sql generation, and knowledge QA. As GenAI products evolve, we are seeking engineers to drive the next phase of development, focusing on enhancing LLM quality, expanding GenAI capabilities, and strengthening platform architecture for AI interactions at scale.

$190k - $285k

Applied Intuition

Applied Intuition is building a robot learning platform to enable any robot to learn industrial tasks and continuously improve. The robotics team develops this platform and uses it to deliver robot autonomy on customer lines, training, evaluating, and deploying policies on real robots performing industrial tasks. This role involves hands-on work with hardware, seeing your contributions reach customers, and working on manipulation policies from task definition to reliable execution on a physical robot. You will train and fine-tune policies, diagnose failures, and ensure their dependability for customer use, with success measured on the robot itself.

$150k - $300k

We are seeking a Senior Machine Learning Engineer to join our Clinical Team. In this role, you will be responsible for owning the tissue-class segmentation and labeling models for our ultrasound CT clinical analysis layer, along with the pipelines that support their training and verification. You will retune models as image inputs are updated and clinical indications expand, and define training/evaluation pipelines, datasets, and metrics from the ground up. A key part of this role involves collaborating with data labeling contractors, expert clinicians, and internal teams on labeling specifications, quality control, and dataset versioning. You will also play a crucial part in productionizing models into a versioned, HIPAA-bound analysis service, ensuring reproducible inference, per-prediction confidence, drift monitoring, and safe fallbacks.

$237k - $250k

NVIDIA is seeking a Senior Integration Engineer to join their autonomous driving team. This role focuses on accelerating the development, integration, evaluation, and deployment of end-to-end driving models. You will collaborate across model development, data, simulation, systems software, and vehicle engineering teams to transform evolving AI models into reliable autonomous driving functionality on NVIDIA's computing platforms. The position involves working with large-scale training infrastructure, simulation environments, and production vehicle platforms.

$152k - $288k

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SpaceXAI is building Super Intelligence to help humanity understand the universe, from supercomputers to Grok models and their suite of applications. The RL Environments team is seeking a Software Engineer to build systems that transform real-world data into high-quality environments and tasks for reinforcement learning. This role involves creating more realistic training environments and owning the platforms and quality layers for trustworthy data production at scale. You will collaborate closely with ML Platform and research teams to convert various data sources into training-ready environments, making high-quality RL data more accessible for model training efforts.

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