Top Machine Learning Jobs in San Francisco Bay Area, CA

The Staff Machine Learning Engineer will design and launch AI-driven tools, collaborate with diverse teams, and innovate in AI solutions to enhance customer value and drive product strategy at Block.

Join Freed as an ML Engineer to optimize speech recognition models and infrastructure. Contribute to AI solutions improving clinician satisfaction.

The role involves developing predictive models, applying machine learning for marketing insights, and executing experiments to evaluate campaign impacts.

Lead the Applied Machine Learning team for Cash App, managing ML engineers, developing AI tools, and fostering collaboration on data-driven insights.

The Senior Machine Learning Engineer will build AI-driven customer support products, collaborate cross-functionally, and maintain large-scale ML systems, leveraging modern techniques for real-world impact.

Design and implement ML-powered features, optimize algorithms, and collaborate cross-functionally to elevate the ML platform and enhance user experiences.

Develop and deploy AI/ML models and pipelines for various applications, optimize them for performance and cost, and collaborate with teams on deployment.

The ML Engineer will manage the infrastructure for training ML models, optimize performance, and ensure scalability for large datasets in collaboration with research teams.

Lead and mentor a team of applied ML engineers at Cash App, focusing on building explainable ML systems to support decision-making across business teams.

Manage and lead a team of Analysts, focusing on marketing measurement, optimizations, and utilizing machine learning to enhance campaign performance for clients.

The Machine Learning Engineer will build and deploy data products, collaborate cross-functionally, improve customer experiences, and mentor others in AI methods.

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.

Lead the technical vision for Upstart's ML and simulations platform, modernizing infrastructure and mentoring a team while collaborating cross-functionally.

Lead KYC modeling strategy, develop machine learning systems for customer onboarding and compliance, and oversee KYC monitoring and rules engine. Manage a team and align strategies with key stakeholders.

The role involves building machine learning models to detect risky activities, collaborating with cross-functional teams, and enhancing modeling capabilities. Candidates should have extensive experience in machine learning and strong analytical skills.

As a Machine Learning Engineer, you'll design, implement, and productionize machine learning models and applications, collaborating with cross-functional teams to solve real-world problems.

The Machine Learning Lead will manage technology strategy for AI training data, develop models, optimize pipelines, ensure dataset quality, collaborate cross-functionally, and mentor engineers.

Lead the design and deployment of machine learning models for personalized navigation, collaborate across teams, and drive technical excellence in ML practices.

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.

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.

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

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

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.

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.

Lead development of advanced recommendation systems, driving ML innovation, maintaining ML pipelines, and collaborating across teams to enhance user engagement.