Top Machine Learning Jobs in San Francisco Bay Area, CA

The role involves building and improving systems for training AI models, focusing on algorithms and infrastructure for reinforcement learning. Responsibilities include enhancing performance, reliability, and usability of systems to support research.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

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.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

The role involves collaborating across departments to build AI-driven models, optimizing data for decision support, and developing scalable solutions for business growth.

The ML Engineer will contribute to the automated discovery engine, developing RL frameworks, synthetic data engines, and evaluating performance using proprietary datasets.

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 Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

Lead a team to advance performance marketing through machine learning and data-driven strategies, optimizing budget allocation and measuring impact.

Design and implement scalable data pipelines and ML algorithms to optimize StackAdapt's digital advertising platform. Collaborate with teams to solve complex problems.

The role involves building end-to-end modeling pipelines, developing models, delivering insights to stakeholders, and collaborating with a technical team in a fast-paced environment.

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 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.

As an Applied Machine Learning Scientist, you will innovate and develop machine learning algorithms, write production code, and collaborate to implement and test these solutions based on historical data.

Develop and scale learning models for behavior cloning and reinforcement learning. Build data pipelines and evaluate model performance for integration into autonomous systems.

Senior Machine Learning Engineer role focusing on building and improving AI evaluation infrastructures, collaborating with a multidisciplinary team, and contributing to the development of a scalable evaluation platform.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

The role involves designing and implementing reinforcement learning pipelines for AI systems, integrating organizational data, and collaborating with product teams to enhance AI functionalities.

Manage a team of Machine Learning Engineers, architecting systems for content integrity, and ensuring effective model training and deployment.