Machine Learning Engineer Jobs in San Francisco, USA

Machine Learning Engineer, Speech LLM Training - San Francisco at Plaud. Apply via Ashby.

Machine Learning Engineer at Orchard. Apply via Ashby.

Senior Machine Learning Engineer at Orchard. Apply via Ashby.

<h2><strong>About Black Forest Labs</strong></h2> <p>We're the team behind Latent Diffusion, Stable Diffusion, and FLUX — foundational technologies that changed how the world creates images and video. Our models power the tools used by millions of creators, developers, and businesses worldwide, and FLUX is among the most advanced generative systems in the world.</p> <p>Headquartered in Freiburg, Germany with a growing presence in San Francisco, we're scaling fast while staying true to what makes us different: research excellence, open science, and building technology that expands human creativity.</p> <h2><strong>Why This Role</strong></h2> <p class="whitespace-normal break-words">You'll live at the intersection of cutting-edge research and brutal production reality. Your customers won't just want FLUX to work—they'll need it optimized for their specific hardware, fine-tuned for their unique use cases, and integrated into systems that weren't designed for diffusion models in the first place.</p> <h2><strong>What You'll Work On</strong></h2> <ul class="[&:not(:last-child)_ul]:pb-1 [&:not(:last-child)_ol]:pb-1 list-disc space-y-2.5 pl-7"> <li class="whitespace-normal break-words">Ensures FLUX models perform optimally in customer environments—whether that's on-premise GPU clusters or BFL-hosted infrastructure—balancing the eternal tension between latency and output quality</li> <li class="whitespace-normal break-words">Architects deep product integrations that go far beyond "here's an API endpoint"—helping customers with everything from model hosting and deployment to inference optimization techniques that haven't made it into textbooks yet</li> <li class="whitespace-normal break-words">Customizes our foundation models for visual media to solve problems customers couldn't articulate until you helped them understand what's possible</li> <li class="whitespace-normal break-words">Sits in technical deep-dives with customers to diagnose performance bottlenecks, then translates those findings into solutions (and sometimes into research questions for our core team)</li> <li class="whitespace-normal break-words">Discovers where generative visual AI should go next by understanding what industries are struggling with problems we could solve</li> </ul> <h2><strong>What We're Looking For</strong></h2> <p class="whitespace-normal break-words">You understand diffusion models not just conceptually, but viscerally—you've debugged them, optimized them, served them at scale. You've been in the room when a customer's integration goes wrong and you need to diagnose whether it's a model issue,

<p><strong>About the Role:</strong></p> <p>The Machine Learning team at Tubi drives the innovation behind personalized user experiences.  With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming.</p> <p>We are seeking a highly skilled <strong>Machine Learning Engineer</strong> to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions.</p> <p><strong>What You'll Do:</strong></p> <ul> <li>Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience</li> <li>Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas</li> <li>Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment</li> <li>Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences.</li> <li>Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement</li> </ul> <p><strong>Your Background:</strong></p> <ul> <li>8+ years of industry experience building production Machine Learning systems</li> <li>MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field</li> <li>Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks</li> <li>Proficiency in building and deploying full-stack machine learning pipelines: data extraction, data mining, model training, feature development, testing, and deployment.</li> <li>Solid understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning.</li> <li>Ability to deep dive into individual components and systems, as well as understand the overall architecture of machine learning solutions.</li> </ul> <p>#LI-Hybrid #LI-SC1</p><div class="content-pay-transparency"><div class="pay-input"><div class=&qu

<p>At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.</p> <p>With over half a billion rides and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Trust & Safety, Growth and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building next-generation platform for low-cost, ultra-immersive transportation to improve people’s lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business.</p> <p>If you are a critical thinker with experience in machine learning workflows, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. </p> <p>As a machine learning engineer, you will be developing and launching the algorithms that power the platform’s core services and impactful products. Compared to similarly-sized technology companies, the set of problems that we tackle is incredibly diverse. They cut across transportation, economics, forecasting, mapping, safety, personalization, and adaptive control. We are hiring motivated experts in each of these fields. We’re looking for someone who is passionate about solving problems with data, building reliable ML systems, and is excited about working in a fast-paced, innovative, and collegial environment.</p> <h2><strong>Responsibilities:</strong></h2> <ul> <li>Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact</li> <li>Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing problems</li> <li>Develop statistical, machine learning, or optimization models</li> <li>Write production quality code to launch machine learning models at scale</li> <li>Evaluate machine learning systems against business goal</li> </ul> <h2><strong>Experience:</strong></h2> <ul> <li>B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience</li> <li>5+ years of Machine Learning experience</li> <li>Passion for building impactful machine learning models leveraging expertise in one or multiple fields.</li> <li>Proficiency in Python, Golang, or other programming language</li> <li>Excellent communication skills and fluency in English</li> <li>Strong understanding of Machine Learning methodologies, including su

Machine Learning Engineer (Foundation Models & Personalization) at Eightsleep. Apply via Ashby.

<div class="content-intro"><p>Kodiak Robotics, Inc. was founded in 2018 and has become a leader in autonomous ground transportation committed to a safer and more efficient future for all. The company has developed an artificial intelligence (AI) powered technology stack purpose-built for commercial trucking and the public sector. The company delivers freight daily for its customers across the southern United States using its autonomous technology. In 2024, Kodiak became the first known company to publicly announce delivering a driverless semi-truck to a customer. Kodiak is also leveraging its commercial self-driving software to develop, test and deploy autonomous capabilities for the U.S. Department of Defense.</p></div><div> <p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Kodiak is seeking Staff Machine Learning Engineers, focusing on model deployment to help build the intelligence that powers the Kodiak Driver. Our ML teams work across perception, prediction, planning, and AI infrastructure to turn real-world driving data into models that enable safe and scalable autonomous trucking.</span></p> <p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">In this role, you will design and deploy machine learning systems that improve our vehicles’ ability to understand the world, predict the behavior of other road users, and make safe driving decisions. You will collaborate closely with robotics, autonomy, and infrastructure teams to continuously improve the performance of our autonomy stack using large-scale data from our growing fleet.</span></p> <span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">This is a high-impact opportunity to work on cutting-edge AI systems operating in the real world, where every mile driven improves our models and brings autonomous trucking closer to global deployment.</span><br><br><span style="font-size: 12pt; font-family: helvetica, arial, sans-serif;"><strong>In this role, you will:</strong></span></div> <ul data-list-tree="true" data-indent="0" data-border="0"> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Help design, train, with a focus towards deploying onboard machine learning models that improve the performance/latency of the Kodiak autonomy stack which includes quantization, pruning, converting to ONNX/TensorRT, custom GPU kernels and profiling.</span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Help identify and achieve parity between onboard and de

<h2>About Wholesail ⛵️</h2> <p>Wholesale trade, a $55T global market, still operates like the world before the internet and modern payment networks: collection processes are manual and run on paper, short-term credit risk is assumed by the vendor, and businesses rely heavily on legacy ERP systems that don't talk to each other. The result is large, measurable drag — we estimate that vendors spend over $500B a year globally across industries on an inefficient mix of processing, bad debt, lending, credit insurance, software, and labor costs to get paid.</p> <p>Wholesail is building a financial network from the ground up that connects the systems of vendors and buyers involved in wholesale trade to enable streamlined payment and the transfer of risk to third parties. This will allow vendors to offload risk and eliminate tens of billions of waste — while giving creditworthy buyers better terms and third-party capital, unlocking hundreds of billions (ultimately trillions) in additional sales. The primitives of this network scale across industries and geographies: a universal approach to ERP integrations, modern payment rails, and a live trade-credit bureau to underwrite risk — which we're calling <a href="https://www.paywholesail.com/features/lighthouse/">Lighthouse</a>.</p> <h2>The Opportunity: Risk & Capital Products 🚢</h2> <p>Credit is the load-bearing beam of our network. Every time a vendor ships goods before getting paid, someone is taking a risk — today it's the vendor, tomorrow it should be a third party at a fair price. Getting that transfer right is what unlocks the next order of magnitude of sales across the wholesale economy, and the only way to get it right is to underwrite buyers more accurately than anyone else in the industry. Listen to the <a href="https://www.acquired.fm/episodes/visa">Visa episode</a> of the Acquired podcast to learn how credit card networks did this for retail trade. </p> <p>We think we're uniquely positioned to do this. Through Lighthouse, we're building a live, reciprocal trade-credit bureau: vendors on our network contribute real-time payment behavior on a long tail of SMB buyers that no traditional bureau sees. That data — combined with the bank, ERP, and transaction signals already flowing through Wholesail — is a modeling dataset that doesn't exist anywhere else. The first MLE on this team gets to decide what we build with it.</p> <p>The problems are real and the stakes are significant. Our models directly shape the terms buyers are offered and the losses Wholesail and our capital partners absorb. There's no established playbook here and no legacy stack to inherit — you'll be setting the direction for how we do modeling, data engineering, and production ML at Wholesail for years to come.</p> <h2>The Role ⚒️</h2> <p>As

Applied Machine Learning Engineer at Inference. Apply via Ashby.

<div class="content-intro"><h2><span style="font-size: 18pt;"><strong>About Taskrabbit:</strong></span></h2> <p>Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more.</p> <p>At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world.</p> <p>Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed!</p></div><p><strong>We are not able to provide visa sponsorship (including H-1B, OPT, or other employment-based visas) for this position. Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. </strong></p> <h3><strong>About the Role</strong></h3> <p>Machine Learning is a cornerstone at Taskrabbit, and we're looking for a seasoned Senior Machine Learning Engineer to join our team and help shape the future of ML/AI at Taskrabbit. This is a unique, full-stack role for an individual who is passionate about the entire machine learning lifecycle—from initial research and model development to building the robust infrastructure required to deploy and scale your work.</p> <p>As a Senior Machine Learning Engineer, you will tackle exciting challenges that directly impact how people discover and connect with home services on the Taskrabbit platform. You will play a crucial role in advancing our capabilities in areas like search ranking, content discovery, and recommender systems. You will collaborate closely with data scientists and other engineers to design and implement novel algorithms, and you will partner with software engineers to ensure the scalability, reliability, and optimization of our models in production.</p> <h3><strong>What You'll Work On:</strong></h3> <ul> <li><strong>Model Development & Research:</strong> Research, design, and implement machine learning models to solve key business problems in areas like search ranking, recommendations, and content discovery.</li> <li><stro

Machine Learning Engineer, Growth at Whatnot. Apply via Ashby.

About Tahoe Therapeutics Tahoe Therapeutics is a biotechnology company pioneering a fundamentally new approach to drug discovery, one that begins with the biology of real patients. Our Mosaic platform is the first to make in vivo data generation scalable, with single-cell resolution, allowing us to map how drugs affect patient-derived cells in the body across a wide range of biological contexts. We are building the world’s largest in vivo single-cell perturbation atlas and using it to train multimodal foundation models that learn the context-dependent nature of gene function, disease progression, and drug response. By combining cutting-edge machine learning with the most biologically relevant datasets ever assembled in drug discovery, our mission is to find better drugs, faster and bring them to more patients who need them. Your role With Tahoe-100M, we solved one of the fundamental bottlenecks in building a virtual model of the cell: generating massive, perturbation-rich, single-cell datasets that capture real biological causality. With Tahoe-x1, we removed the second bottleneck: creating a modern platform for rapid iteration on model architectures and designs in a cost-efficient manner and at scale. At Tahoe, we embody a simple philosophy: build in the open, shoot for the moon, and we’re looking for people who want to push the frontier of what’s possible. As a Senior Machine Learning Engineer, you will play a leading role in designing the next generation of foundation models of gene regulatory networks powered by Tahoe’s large scale single-cell datasets such as Tahoe-100M and beyond. This role is well-suited for someone with a strong background in machine learning and statistics, and an interest in applying cutting-edge breakthroughs in ML to meaningful problems in drug discovery. We are looking for non-incremental thinkers with the skills to help build models that can make a real impact on drug discovery.

About Kiddom Kiddom is a groundbreaking educational platform that promotes student equity and growth by uniting high-quality instructional materials with dynamic digital learning. Through unparalleled curriculum management functionality, Kiddom empowers schools and districts to take ownership of their curriculum – resulting in learning experiences tailored to meet the unique needs and goals of local communities. Kiddom’s high-quality curriculum is layered with robust teacher and leader data insights to drive the continuous improvement of instructional decisions, school/district programming, and professional learning. What the job involves   You will be part of Kiddom’s AI team, building the foundation of our search, recommendation, and insights systems. Your work will directly support teachers and students by delivering timely insights, personalized content, and intelligent assistance.

About Hive Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive’s solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more. Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI! Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.

About Hive Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive’s solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more. Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI! Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.

About Hive  Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive’s solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more. Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI! Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.

Senior Machine Learning Engineer at Arcade. Apply via Ashby.