Top Machine Learning Jobs in San Francisco Bay Area, CA

The Machine Learning Engineer will build models to detect fraud in Block's ecosystems, collaborate with teams, and enhance ML processes.

Lead centralized Machine Learning efforts at Affirm, managing model development lifecycles, fostering AI adoption, and overseeing a team of ML professionals to enhance business outcomes.

Develop advanced ML models for an advertising platform, focusing on performance and scalability. Lead technical strategy and collaboration across teams to enhance campaign automation and optimization.

The Principal Machine Learning Engineer will lead the Content Relevance team in optimizing personalized video recommendation systems, advancing core ML capabilities, and collaborating on tech strategies. This role also involves mentoring, technical direction, and applying best practices for system performance.

Design and deploy machine learning models to estimate weather conditions using camera, lidar, and radar data. Collaborate with teams to address weather-related needs and build evaluation systems for rapid deployment.

Lead the development of ranking and relevance models, design ML systems for patient-provider matching, and mentor junior team members.

As a Senior Software Engineer specializing in Machine Learning, you will design and scale Braze's AI platform, focusing on data architecture and production-level ML implementations.

Lead a team focused on machine learning solutions, overseeing project execution, designing AI/ML infrastructure, and mentoring engineers towards excellence in scalable ML implementations.

The Machine Learning Engineer will scale core infrastructure, manage data pipelines and model evaluation, and improve benchmarking systems. Collaborate with teams to enhance AI evaluation methodologies.

Manage and lead a team in developing machine learning algorithms for driving models. Oversee strategy, technical guidance, performance monitoring, and resource allocation for Offline ML models.

As a Machine Learning Engineer, you'll develop and ship models for an AI platform, own projects from start to finish, and work closely with customers to enhance product features.

As an Applied Scientist II, you will work with cross-functional teams on projects that optimize software systems and improve ML components, while analyzing inefficiencies and proposing solutions.

Design and maintain ML pipelines and data pipelines, optimize fraud detection models, collaborate with teams, and ensure data quality for high-scale applications.

As a Staff Machine Learning Engineer, you will design and develop ML systems to combat fraud by building data pipelines, integrating data sources, and ensuring high-quality model performance while collaborating with teams.

The Staff Machine Learning Engineer will define technical strategies, design ML models for document processing and risk assessment, and build scalable ML systems to protect Coinbase users' funds.

The Staff Machine Learning Engineer will utilize AI models, mentor team members, and enhance automation solutions across Coinbase's operations, focusing on machine learning to solve complex challenges.

Develop and deploy machine learning models for risk assessment, collaborating with teams to enhance Gusto's product offerings while ensuring model performance and reliability.

As a Machine Learning Systems Engineer, you will build and scale AI infrastructure, leading projects and mentoring junior engineers, while focusing on the ML project lifecycle and system architecture.

Lead the development of machine learning models for advertising products, optimizing strategies and driving business-critical outcomes.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

Develop and implement advanced reinforcement learning methods and distributed systems for AI agents. Collaborate with customers to understand needs and create tailored solutions.

The Staff Machine Learning Engineer will architect and optimize data infrastructure for multimodal AI models in oncology, focusing on data management and processing pipelines.

As a Senior Machine Learning Engineer, you will develop machine learning models, manage their lifecycle, build infrastructure, and collaborate with teams to enhance our capabilities in various ML areas.

Develop machine learning models for search ranking and personalization at Faire, leveraging data to help local retailers thrive.

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.