Top Machine Learning Jobs in San Francisco Bay Area, CA

As a Staff Machine Learning Engineer, you will lead the design, implementation, and optimization of machine learning models, collaborate cross-functionally, and drive AI strategy to enhance SailPoint's identity security solutions.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

As a Machine Learning Intern, you will lead projects, analyze data, build models, and solve complex problems using machine learning and AI techniques.

The Machine Learning Engineer will develop and improve ML models for product surfaces, build data processing pipelines, and leverage machine learning technologies in advertisements.

The Senior Machine Learning Engineer will design and implement ML systems, optimize data pipelines, and collaborate on ML workflows for personal injury legal solutions.

The Staff Machine Learning Engineer will design ML systems, mentor engineers, work on AI product development, and improve legal data processing.

Lead a team of applied data scientists and ML engineers to develop scalable forecasting systems. Collaborate cross-functionally to integrate forecasting insights into decision-making processes and business strategies.

Lead the AI/ML initiatives at Legion, develop forecasting models, manage a team of ML specialists, and engage with clients on tech adoption.

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.

Develop machine learning models to detect and reduce fraud within Block's ecosystems, while collaborating with various teams to implement solutions.

The Senior Machine Learning Engineer will develop and enhance a machine learning platform, supporting data scientists and engineers in building and deploying models. Responsibilities include defining best practices for ML service development, CI/CD management, and collaboration across teams.

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.

Design and implement ML models and systems, collaborate with cross-functional teams, and advance R&D efforts in a fast-paced environment.

Develop machine learning-powered ads ranking models, create performance evaluation metrics, and collaborate with Data Scientists to enhance ad experimentation.

The role involves designing, developing, and deploying machine learning models for healthcare applications, collaborating with cross-functional teams, and optimizing model performance.

Lead a team in developing and optimizing a personalized video recommendation engine, focusing on machine learning infrastructure and A/B testing. Ensure system architecture scalability, performance, and reliability.

As a Staff Machine Learning Engineer, you will design and develop machine learning systems to prevent fraud, ensuring data quality and integrating diverse data sources while collaborating with cross-functional teams.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

As a Staff Applied Machine Learning Engineer, you'll design and implement LLM applications, integrating ML features to enhance user experiences and scalable services.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

Develop and improve machine learning models for Pinterest's various product surfaces, utilizing deep learning and advanced data processing.

Develop and execute ML technology stack vision for Ads, improve ML models, and enhance content understanding using LLMs in a collaborative environment.

The Engineering Manager - Machine Learning will lead a team developing ML models for growth personalization and financial insights, driving measurable impact across Plaid's products.

Lead the design, development, and scaling of machine learning systems to optimize Adobe's go-to-market strategies and improve customer experiences.