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

The role involves developing an AI agent platform, building ML models, and enhancing user experiences with advanced algorithms. Collaboration and fast-paced execution are key.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

Lead and build a Machine Learning team, driving strategy and execution across product areas like Document Generation and Voice Agents while collaborating with Product and Engineering.

Develop and operationalize machine learning models for lab automation, leveraging multimodal data and ensuring reliable predictive capabilities in drug discovery processes.

Lead the Performance ML squad, managing and mentoring engineers while driving the development, deployment, and strategy of predictive models for advertising.

Manage and grow the ML team, define goals and metrics, drive ML initiatives, build evaluation processes, and collaborate cross-functionally to enhance product delivery.

You will lead and manage a team of engineers developing machine learning solutions for perception product challenges in autonomous driving.

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.

As an AI/ML Engineer, develop and optimize analytics frameworks to enhance autonomous vehicle development, focusing on automation tools and collaboration with engineering teams.

Lead the design and deployment of machine learning models for personalized navigation and recommendations, managing projects end-to-end with a focus on user-centric solutions.

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.

Lead the application of reinforcement learning techniques to enhance models for creative tasks. Require strong programming and machine learning project experience with a focus on user interface.

In this role, you'll develop machine learning models for logistics optimization, retailer underwriting, and growth strategies, collaborating with a skilled team to enhance the marketplace experience.

As a Staff Machine Learning Engineer, you'll lead AI product development, leveraging LLMs and embeddings, collaborating on technical strategy and coding performance enhancements.

The Engineering Manager, Machine Learning will lead a team focusing on 3D deep learning and computer vision, manage the ML roadmap, and implement best practices for MLOps pipelines.

Lead the design and implementation of machine learning applications, collaborate with cross-functional teams, optimize ML systems, and ensure responsible AI practices.

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 Staff Machine Learning Engineer will develop classification systems for content and creators, building machine learning pipelines, conducting analyses, and collaborating with cross-functional teams for effective solutions.

The Staff Machine Learning Engineer will lead the design and implementation of conversion models, establish ML best practices, and collaborate with teams to enhance Pinterest's ad performance.

Design, build, and ship ML-powered product features (search, personalization, recommendations, computer vision). Improve ML platform, pipelines, deployment, monitoring, and data infrastructure. Collaborate cross-functionally to define metrics, iterate models, and deliver scalable, reliable ML systems.

Develop and maintain a full-stack platform for computational chemists, focusing on drug discovery through machine learning and data infrastructure. Collaborate with interdisciplinary teams to enhance software tools for visualizing molecules and managing workflows.