Machine Learning Engineer Jobs in San Francisco

NVIDIA is seeking a research engineer to join the Isaac team, focusing on physical AI for robotics. This role involves developing simulation tools for scientists and companies leveraging machine learning in robotics. You will bridge the gap between Isaac product engineering and NVIDIA Robotics research, transforming research concepts into product features and providing user feedback to the research loop. The team works at the intersection of simulation and machine learning, aiming to create the leading tool for evaluating robot foundation models in simulation, building on NVIDIA's expertise in photorealistic rendering and physics simulation.

$184k - $357k

Sieve

Sieve is a multi-modal lab focused on curating high-quality training datasets across video, audio, images, text, and 3D, aiming to solve the bottleneck in the growth of AI applications. As a perception-focused Machine Learning Engineer, you will build systems that transform raw sensor footage into training data crucial for robotics and world-model teams. This role requires a strong background in computer vision, particularly in shipping perception systems for robots, devices, or autonomous vehicles, and applying these skills to massive datasets.

Salary not listed

Nebius is building a full-stack AI cloud platform to support developers and enterprises from data and model training through to production deployment. As a Senior Machine Learning Engineer on the Applied AI team, you will own model and endpoint optimization from model artifacts through production deployment. Your work will span model internals, quantization, model compression, speculative decoding, KV-cache optimization, inference engines, and serving architecture to improve latency, throughput, memory efficiency, GPU utilization, and cost per token while preserving model quality and reliability. You will collaborate with kernel and platform engineers to investigate serving problems, compare configurations, and resolve performance and quality regressions, validating improvements through reproducible benchmarks and safe production rollouts.

$195k - $262k

SambaNova

SambaNova is seeking a Principal Engineer to own kernel-level drivers and low-level software for high-speed IO, memory, and networking subsystems within the DataScale® platform and RDU architecture. This role is central to delivering reliable, high-performance AI systems at scale. This is a hands-on Linux kernel and device driver role; it is not an application or platform software role. You will lead software bring-up of new silicon, deliver production drivers across the IO, memory, and network data paths, and debug complex issues spanning kernel, firmware, and hardware. This role suits an engineer with deep kernel and driver expertise and strong hardware fluency, who can operate in ambiguity and execute with high ownership.

$180k - $255k

Anthropic

As a TPU Kernel Engineer, you will be responsible for identifying and addressing performance issues across various ML systems, including research, training, and inference. A significant part of this role involves designing and optimizing kernels specifically for the TPU. You will also provide crucial feedback to researchers regarding how model changes affect performance. The ideal candidate will have a proven history of solving large-scale systems problems and demonstrating expertise in low-level optimization.

$280k - $850k

Glean is seeking a Software Engineer to help build a scalable software-based platform, including enterprise search solutions. This role involves working across distributed systems, data pipelines, APIs, and user interfaces to deliver secure, high-quality products. You will contribute to a Work AI ecosystem that powers intelligent search, an AI Assistant, and scalable AI agents, leveraging a broad range of enterprise data and flexible LLM choices. The position offers the opportunity to shape how the world works by building systems used daily across major platforms and embedding agentic capabilities into an open, extensible stack.

$215k - $279k

Inworld is a research lab and inference provider focused on real-time AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, real-time workloads. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more, serving over 10 trillion LLM tokens per month. We are looking for strong individuals from varied backgrounds who learn fast, thrive in ambiguity, and can demonstrate their experience in building, breaking, and understanding complex systems.

$250k - $300k

Scale AI

Scale is seeking a Staff Machine Learning Research Engineer to join the Applied Intelligence Systems (AIS) team, which is part of the Scale Generative AI Platform. This role focuses on advancing agentic AI applications for enterprise and government use cases. You will work across the full spectrum of technical challenges within AIS, contributing to areas such as model training and fine-tuning, designing evaluation systems, building improvement loops from production data, prototyping novel agent architectures, and developing internal tooling. This is a hands-on research and engineering position where you will write code, ship production systems, and set the AI/ML technical direction for the team, influencing methods, architectures, and standards for others.

$250k - $350k

Wayve is building the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience. This role sits at the center of our datasets team, which owns the driving data our AI Driver learns from, covering ingestion, annotation, retrieval, and data quality. As our data grows towards exabyte scale, deciding what data to keep and where is a major lever on both model quality and cost. You will shape the data that model engineers train on across the company, defining our dataset content strategy and steering data selection based on current model engineering needs.

$390k - $460k

OpenAI

OpenAI is seeking a senior Machine Learning Data Scientist to lead its forecasting initiatives within the Strategic Finance team. This is a founding role for the Forecasting pillar, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. The models developed will be crucial for predicting key business metrics like daily/weekly active users, revenue, lifetime value, compute consumption, and profitability, directly influencing critical business decisions and company strategy. This role requires a blend of technical expertise, product intuition, and business acumen, involving close collaboration with product managers, researchers, engineers, and finance leaders to operationalize insights and build foundational forecasting capabilities.

$347k - $445k

Salesforce is seeking a Senior/Lead Performance Engineer to join the SalesforceDB team, which manages the transactional database powering the Salesforce Platform. This role involves driving the design, scalability, and performance of our distributed database technology. You will identify and resolve performance bottlenecks, lead benchmarking efforts, and build telemetry to monitor production fleet performance. This is a fast-paced, collaborative environment where your work directly impacts the performance and scalability of a system handling trillions of transactions monthly.

$149k - $260k

Scale AI

Scale works with leading AI labs to accelerate progress in GenAI research, focusing on LLM post-training and evaluation. This role is on the evaluation pod, building benchmarks and diagnosing model failure modes in text and multimodal modalities. You will develop rigorous evaluations to reveal where and why frontier models fail, collaborating with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with foundation model labs to translate failure analysis into technical and strategic input for 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

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 is revolutionizing biomedicine by integrating large-scale automated data generation with advanced AI. We are building a system where AI, automation, and experimental biology work together synergistically. This role focuses on connecting that work to human medicine by developing systems that evaluate the biological validity of clinical programs. You will build the infrastructure to assess mechanistic support, ground biological mechanisms in human data, and evaluate clinical trial designs against proposed mechanisms. The goal is to create scalable systems that can rigorously assess and forecast program outcomes, ensuring scientific integrity and enabling public dissemination of findings.

$268k - $384k

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

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

Lila is revolutionizing medicine by integrating automated large-scale data generation with scientific superintelligence. We are building a system where AI, automation, and experimental biology work together to tackle complex medical challenges. The Life Science AI team focuses on developing machine learning systems for analyzing biological data, combining advanced ML with cutting-edge biology. This role is crucial for building domain models that understand perturbation biology, genetics, and high-dimensional experimental data, linking biological mechanisms, experimental interventions, and therapeutic opportunities. The work involves not just learning from data but also guiding data generation and ensuring model outputs are interpretable and actionable for scientists and downstream systems.

$268k - $358k

Lila Sciences is developing a platform where AI and automation collaborate to address complex challenges in medicine, specifically within Life Sciences AI. The AI for Protein Engineering team focuses on creating and implementing generative and predictive models to advance biomolecule design programs from initial concepts to validated leads. This role is for a senior individual contributor specializing in computational biologics design, working on active protein engineering projects and enhancing Lila's capabilities in designing, evaluating, and learning from biomolecular data. The position is at the nexus of machine learning, protein engineering, and therapeutic design, requiring deep ML expertise, a strong understanding of protein biology, and a proven ability to deliver computationally designed, validated biologics.

$268k - $358k

Lila Sciences is developing a platform where AI and automation work together to tackle complex problems in medicine. The AI for Protein Engineering team focuses on creating and using generative and predictive models to advance biomolecule design programs from initial concepts to validated leads. This role is at the intersection of machine learning, protein engineering, and therapeutic design, requiring strong ML fundamentals, a curiosity for protein biology, and an interest in computationally designed, wet-lab-validated biologics. You will collaborate with experimental scientists, AI researchers, and platform teams to build models and workflows that support Lila’s autonomous science platform.

$176k - $304k

Lila Sciences is building a platform where AI and automation co-evolve to solve complex problems in medicine, specifically in protein engineering. The AI for Protein Engineering team develops models and systems to advance biologics from design to validation. This role involves designing molecules for active biologics programs, developing reasoning capabilities for drug discovery, and creating evaluation infrastructure to ensure design workflows are effective and generalizable across programs. The position requires owning the operational aspects of computational design workflows, including reproducibility, throughput, and inference cost, and translating domain scientist judgment into machine learning objectives.

$176k - $304k

Lila Sciences is building a platform where AI and automation co-evolve to solve complex problems in medicine. Within Life Science AI, Machine Learning engineers build and operate systems that transform foundation models into production capabilities for automated scientific discovery. This Principal ML Engineer role focuses on designing, building, and scaling the ML infrastructure behind these models, with current work in structure prediction, co-folding, sequence design, and multimodal scientific reasoning. You will own critical systems end-to-end, from training pipelines and distributed compute to model deployment and integration into Lila's discovery engine, shaping the technical direction for ML model training, evaluation, and deployment at scale.

$268k - $384k