Top Machine Learning Engineer Jobs in San Francisco, CA

Lead the technical roadmap for the Ad Marketplace, design and optimize machine learning models, and collaborate with teams to meet objectives.

Develop advanced machine learning and statistical models to support credit risk and operational strategies, collaborating with multiple teams to enhance business profitability.

Lead the technical vision and architecture of the trajectory generation planning stack, focusing on real-time planning, safety, and performance metrics. Drive experimentation and mentoring while collaborating with cross-functional teams to improve autonomous vehicle capabilities.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

As a Senior Engineering Manager for ML & AI, you'll lead Data Science and ML initiatives, mentoring team members, and collaborating across R&D to drive strategic AI solutions that impact the business.

As a Machine Learning Engineer, you'll build statistical models, optimize advertiser performance, design experiments, and collaborate across teams to enhance Liftoff's revenue growth.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Lead the SDL and Cash Line ML teams, developing innovative machine learning models to improve lending solutions and expand credit access. Collaborate with cross-functional teams to drive product strategy and enhance model performance, while mentoring a team of ML scientists.

Lead AI/machine learning innovations and advanced analytics for new vehicles. Develop statistical models for pricing and valuation, guiding experiments and communicating insights.

Lead the development of automated ML-driven map reconstruction systems. Architect and implement pipelines to validate and maintain map primitives, ensuring reliability across large-scale deployments.

The Senior ML/AI Modeler will automate risk investigations using AI, improve productivity through technology, and deploy ML systems at scale, while collaborating across teams to enhance performance and decision-making.

The Senior Lead Machine Learning Engineer will design, develop, and implement machine learning systems, collaborating with teams to solve business problems using machine learning applications.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

Lead the design and deployment of machine learning models to detect fraud, collaborating with teams to optimize performance and effectiveness while integrating solutions into existing systems.

Lead development of advanced recommendation systems, driving ML innovation, maintaining ML pipelines, and collaborating across teams to enhance user engagement.

Design and implement forecasting and optimization models, build ML pipelines, collaborate with teams for model integration, and improve data workflows.

As the Area Technical Lead, you will architect and improve the ML data strategy for autonomous driving, enhancing the data-driven self-improvement process for the Waymo Driver.

As a Machine Learning Engineer, you will design and deploy models, collaborate with teams to solve business challenges, optimize performance, and maintain model effectiveness.

Research and develop improvements to machine learning models, collaborate with research and product teams, and evaluate model performance.

Design, prototype, and deploy machine learning models and pipelines to detect environmental changes for Lyft's map. Collaborate with engineers, data scientists, and product teams to analyze data, build POCs, write production-quality code, and evaluate ML systems against business goals.

The Machine Learning Engineer will design, develop, and implement advanced recommendation systems, collaborating with cross-functional teams to enhance personalization for a global audience.

As a Founding AI Engineer, you will develop an AI-powered knowledge platform, focusing on backend systems, machine learning data pipelines, and optimizing tech stack for performance while participating in the entire product lifecycle.

The Senior Machine Learning Engineer will design innovative machine learning models for drug discovery, leveraging large-scale single-cell datasets and collaborating with ML Scientists to develop optimized models.

The Senior AI Scientist will lead ML/AI innovation for multimodal video models, develop production-grade ML models, and engage in research and representation at conferences.

The Senior Manager will develop and deploy machine learning pipelines to enhance clinical trial operations, ensuring AI integration into business processes while managing stakeholder engagement and AI product lifecycles.