Top Remote Machine Learning Jobs in San Francisco Bay Area, CA

As a Machine Learning Engineer, you'll evaluate neural network quality, coordinate with researchers, manage experiments, and report results to streamline AI software development.

Lead the design and implementation of ML models and systems for auto-labeling in robotics. Collaborate across teams and mentor junior engineers.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

You will build frameworks for LLM-powered agents, design reinforcement learning approaches, lead development of scalable evaluation systems, and mentor other engineers while writing robust code for enterprise-grade assistants.

The Senior Machine Learning Platform Engineer will build foundational components for ML models, mentor junior engineers, and optimize streaming pipelines. Responsibilities include enhancing ML infrastructure and ensuring data quality.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

Lead training, evaluation, and deployment of ML models for scene understanding and behavior prediction in autonomous vehicles.

You will train, evaluate, and deploy ML models for scene understanding and behavior prediction in autonomous vehicles, while collaborating with engineers.

Join Trexquant as a Global Alpha Researcher to develop trading signals, implement research, and apply machine learning for alpha discovery.

Design and deploy machine learning systems for autonomous vehicles, collaborating with teams to improve model performance and safety using real-world data.

The role involves developing ML systems for enterprise workflows, focusing on user understanding, task prediction, and optimizing ML pipelines. Key responsibilities include designing scalable evaluation frameworks and collaborating with teams to deliver production-ready solutions.

Lead cutting-edge machine learning research, develop algorithms, and deploy production-ready models in a healthcare-focused AI environment. Collaborate with engineers and clinicians to optimize healthcare systems.

Design and deploy machine learning models for personalized recommendations and search on Zillow's platforms. Collaborate with cross-functional teams to enhance user experience.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Lead development and production deployment of advanced ML and time-series models for water and infrastructure systems, perform research in Physical AI, collaborate cross-functionally, communicate impact to stakeholders, and mentor junior data scientists.

As a Senior ML Engineer, you'll own ML-driven features from modeling to deployment, drive innovation in generative AI, and mentor junior members.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

As a Cloud Machine Learning Engineer at Hugging Face, you will build ML solutions leveraging cloud technologies, integrate models, design APIs, and contribute to documentation and community advocacy.

The role involves leading ML strategy, architecting systems, designing algorithms, collaborating with teams, and mentoring engineers in AI for enterprise analytics.

The AI & Machine Learning Director will lead client engagements, analyze corporate performance, and drive improvements in profitability through machine learning and data analysis, while also managing business development and team collaboration.

Lead the Applied Machine Learning team at ExtraHop to develop systems for behavioral detection in network security. Manage model design, evaluation, and operationalization while maintaining experimental rigor and collaborating with product teams.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.

The role involves designing and implementing machine learning systems for knowledge representation and temporal reasoning, focusing on organizational intelligence. Responsibilities include building LLM-powered pipelines, developing memory algorithms, and researching various ML techniques.

The ML Engineer will develop and enhance machine learning models for credit decisioning, drive technical innovation, and collaborate across teams to deliver impactful solutions for small businesses.