Machine Learning Engineer Jobs in San Francisco, USA

<div class="content-intro"><h2><strong>About Goodfire</strong></h2> <p>Goodfire is a research company using interpretability to understand, learn from, and design AI systems. Our mission is to build the next generation of safe and powerful AI—not by scaling alone, but by understanding the intelligence we're building.<br><br>Scaling has proven powerful, but today's approach is fundamentally limited: we can't meaningfully understand, debug, or shape what models learn. Every engineering discipline has been gated by fundamental science and AI is at that inflection point now.</p> <p>We're advancing the science of how AI systems actually work. Treating models as black boxes is an unnecessary handicap—we have access to the structures inside them, and understanding those structures lets us steer what models learn, make them safer and more useful, and extract the vast knowledge they contain. Our goal is to make AI that can be understood, debugged, and shaped like software.</p> <p>Goodfire is a public benefit corporation headquartered in San Francisco with a team of the world’s top interpretability researchers and engineers from organizations like OpenAI and DeepMind. We're backed by over $200M from B Capital, Menlo Ventures, Lightspeed, Eric Schmidt, and others.</p></div><h2><strong>About the role</strong></h2> <p>We’re looking for Machine Learning Engineers to help build our platform for training, evaluating, and deploying interpretable AI systems at scale. You’ll play a central role in building our core technology, from training and eval tooling to product features, to achieve our mission of understanding and intentionally designing AIs.</p> <p><strong>Where you might contribute:</strong></p> <ul> <li><strong>Interpretability tools</strong> – Building the tools and infrastructure to support understanding and intentional design of models at industry scale.</li> <li><strong>Training infrastructure</strong> – Extending and supporting our training infrastructure for large training runs.</li> <li><strong>Product</strong> – Turning state of the art interpretability research into robust, usable product features.</li> </ul> <p>We'll work with you to determine the team that best aligns with your strengths.</p> <p><strong>Key responsibilities:</strong></p> <ul> <li>Turn cutting edge interpretability research into production ready tools.</li> <li>Optimize pipelines and infrastructure for frontier model interpretability, training, and inference.</li> <li>Integrate new machine learning workflows and pipelines into our product and deploy to customers.</li> <li>Ensure system reliability, reproducibility, and performance.</li&

<div class="content-intro"><h2>About us</h2> <div>PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.</div> <div>We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.</div></div><p><strong>Note: </strong>We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.</p> <h2><strong>Who We're Looking For</strong></h2> <p>As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.<br><br>You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.<br><br>With at least 2 years industry experience (post Masters or PhD) in a commercial, non-research environment. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.</p> <p>We have hybrid offices in London, New York, and Singapore; this role is hybrid based in the San Francisco area.</p> <h2>This Role </h2> <p>As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.</p> <div><strong>What you will do </strong></div> <ul> <li>Work closely with our simulation engineers, data scientists and customers to develop an understanding of the

<div class="content-intro"><p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.</span></p></div><p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><strong>The Community You Will Join: </strong></span></p> <p>Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. </p> <p>The Community Support Products (CSP) Machine Learning team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search,  LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. </p> <p>The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to investing in long term innovation to solve the complex problems we face, and to do that we need the very best experts in ML and AI to join us.</p> <p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><strong>The Difference You Will Make:</strong></span></p> <p>We believe our current customer experiences in these domains are only scratching the surface of the innovations that are possible, and that science is at the heart of delivering a step-function change for our Guest and and Host on Airbnb. </p> <p>You will build and leverage cutting edge AI technologies to transform Airbnb’s customer service by delivering personalized, easy-to-use and proactive customer service experience. </p> <p>Many of the initiatives you’ll tackle are in their early conceptual stages. You will have the opportunity to shape these ideas from inception to production, turning visionary concepts into impactful realities.</p> <p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><strong>A Typical Day: </strong></span></p> <ul> <li>Envision

<div class="content-intro"><p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.</span></p></div><p><strong>The Community You Will Join:</strong></p> <p>Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. </p> <p>The Core ML team in Community Support is the team responsible for adopting the Agentic AI technologies to enable an intelligent, scalable and exceptional customer service experience. We are responsible for developing the Chat AI assistant, Voice AI Assistant and more! The team is constantly exploring the SOTA Agentic architecture, develops and enhances various AI models, ML services and leverages tools including SFT, Reinforcement learning, Distillation, RAG/Search,  LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. </p> <p><strong>The Difference You Will Make:</strong></p> <p>We believe our current customer experiences in these domains are only scratching the surface of the innovations that are possible, and that science is at the heart of delivering a step-function change for our Guest and and Host on Airbnb. <br>You will build and leverage cutting edge AI technologies to transform Airbnb’s customer service by delivering personalized, easy-to-use and proactive customer service experience. <br>Many of the initiatives you’ll tackle are in their early conceptual stages. You will have the opportunity to shape these ideas from inception to production, turning visionary concepts into impactful realities.</p> <p><strong>A Typical Day: </strong></p> <ul> <li>Champion the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems</li> <li>Work cross-functionally with product, design, and other engineering counterparts to design and build efficient AI solutions for Airbnb CS products</li> <li>Learn and share the latest AI/ML technologies with the team.</li> </ul> <p><strong>Your Expertise:</strong></p> <ul> <li><em>(Required)</em> PhD or 3+ YOE in Computer Science, Machine Learning, Statistics, Artificial Intelligence, or a related technical field — or equi

Machine Learning Engineer, Distributed Data Systems - Robotics at Openai. Apply via Ashby.

Machine Learning Engineer, Integrity at Openai. Apply via Ashby.

<p>P-1504</p> <p>The Applied AI team at Databricks sits at the forefront of advancing GenAI-powered products. Over the past years, we’ve launched <a class="c-link" href="https://www.databricks.com/blog/introducing-databricks-assistant" target="_blank" data-stringify-link="https://www.databricks.com/blog/introducing-databricks-assistant" data-sk="tooltip_parent">Databricks Assistant</a>, <a class="c-link" href="https://www.databricks.com/product/ai-bi/genie" target="_blank" data-stringify-link="https://www.databricks.com/product/ai-bi/genie" data-sk="tooltip_parent">AI/BI Genie</a>, and <a class="c-link" href="https://www.databricks.com/blog/introducing-agent-bricks" target="_blank" data-stringify-link="https://www.databricks.com/blog/introducing-agent-bricks" data-sk="tooltip_parent">Agent Bricks </a>working with product teams, and made significant strides in LLM quality for these products. These products are used by 100s of thousands of Databricks users every day. We are tackling challenging problems like code suggestion, error detection and correction, text-to-sql generation, automatic pipeline generation, knowledge QA and many others.</p> <p>As our GenAI products continue to evolve, we are seeking multiple <strong> GenAI Engineers from junior levels to more senior levels</strong> to drive the next phase of development. In 2025, we will focus on enhancing LLM quality, expanding GenAI capabilities across Databricks products, and strengthening our platform architecture to enable seamless AI interactions at scale.</p> <p><strong>Key Responsibilities</strong></p> <ul> <li>Shape the direction of our applied AI areas and intelligence features in our products<strong>. </strong>Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products and services (e.g., Databricks Assistant and AI/BI Genie).</li> <li>Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains.</li> <li>Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration.</li> <li>Work closely with cross-functional teams, including AI researchers, ML engineers, and product teams, to deliver impactful AI solutions that enhance user productivity and satisfaction.</li> <li>Build scalable, reusable backend systems to support GenAI products across the company. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable mod

<p>P-984</p> <p>Founded in late 2020 by a small group of machine learning engineers and researchers, Mosaic AI enables companies to securely fine-tune, train and deploy custom AI models on their own data, for maximum security and control. Compatible with all major cloud providers, the Mosaic AI platform provides maximum flexibility for AI development. Introduced in 2023, Mosaic AI’s pretrained transformer models have established a new standard for open source, commercially usable LLMs and have been downloaded over 3 million times. Mosaic AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.</p> <p>Now part of Databricks since July 2023, we are passionate about enabling our customers to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI platform so our customers can use deep data insights to improve their business. We leap at every opportunity to solve technical challenges, striving to empower our customers with the best data and AI capabilities.</p> <p><strong>Summary: </strong></p> <p>Databricks Mosaic AI is hiring experienced machine learning platform engineers to build out our customer-facing generative AI platform for the ML development lifecycle including data generation, training, evaluation, serving, and agent-building.</p> <p>You will thrive in this role if you have a strong sense of end-to-end ownership and enjoy translating user requirements into product interfaces and building the backend distributed systems to power those interfaces. In this role, you will have the opportunity to contribute to all areas of our stack spanning from user-facing features to low-level GPU orchestration.</p> <p>You will:</p> <ul> <li>Play a key role in the end-to-end design and implementation of our product which is a platform for powering use cases across training and serving of generative AI models</li> <li>Work closely with both customers and internal ML researchers to identify key areas of development for our generative AI platform</li> <li>Have strong end-to-end product ownership, translating product requirements into user interfaces and backend distributed system design and own end-to-end implementation</li> <li>Design and build the core platform infrastructure that supports our customer-facing product features</li> <li>Ensure the reliability, security, and scalability of the backend distributed systems that power all aspects of our product</li> </ul> <p>We look for:</p> <ul> <li>4+ years of hands-on programming experience with at least one modern language such as Python, Scala, Go,

Machine Learning Engineer at Latent. Apply via Ashby.

Staff Machine Learning Engineer, Community Support Engineering at Airbnb. Apply directly on Airbnb's jobs board.

Machine Learning Engineer, Community Support Engineering at Airbnb. Apply directly on Airbnb's jobs board.