Top Machine Learning Jobs in San Francisco Bay Area, CA

As a Senior Machine Learning Engineer, you'll design and manage ML infrastructure, work with Data Science to implement models, and oversee system health and reliability.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

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.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

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.

The role involves developing ML models, conducting experiments, and optimizing car assignments to improve Waymo's Marketplace efficiency.

As a Staff Machine Learning Engineer, you'll design large-scale recommendation and retrieval systems, enhance quizlet's personalization through ML, collaborate with teams, and ensure models align with user outcomes.

As an Applied Scientist at Lyft, you will develop ML and optimization models for dynamic pricing, collaborate across teams, and implement algorithms to enhance rider experience.

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.

This role involves building and optimizing ML systems and frameworks, collaborating with teams to enhance research and development in ML models.

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.

The role involves implementing ML models, building data pipelines, and quickly iterating on experiments in a team focused on causal intelligence for weather prediction.

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

Lead the Enterprise ML team, defining research roadmaps, mentoring scientists, communicating research outcomes, and driving impactful AI systems in a fast-paced environment.

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.

Design and deploy ML models for fraud detection, develop data pipelines, partner with teams to ensure effective fraud prevention, and enhance detection accuracy.

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.

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.

Develop mathematical models for discounting systems, collaborate on algorithms, analyze data, and improve rider engagement products while working with cross-functional teams.

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