Top Machine Learning Jobs in San Francisco Bay Area, CA

The Principal AI Engineer is responsible for establishing AI governance frameworks, overseeing compliance, and advising senior leadership on AI initiatives in a highly regulated environment.

As an AI Engineer, you will develop and optimize AI systems for legal tasks, work on integrating models, and establish evaluation frameworks to enhance decision-making capabilities in complex legal workflows.

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

The Data Scientist will collaborate with various teams, run experiments, analyze data to inform product strategy, and drive growth through advanced analytics and machine learning.

As a Senior Lead AI Solutions Consultant, you will drive revenue by promoting the Braze AI tools, collaborate with stakeholders, conduct AI Academy programs, and serve as a thought leader in AI technologies.

Lead the development of automated ML-driven map reconstruction systems. Architect and implement pipelines to validate and maintain map primitives, ensuring reliability across large-scale deployments.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

In this role, you will develop AI foundation models, perform applied research, collaborate with cross-functional teams, and leverage advanced technologies to enhance customer experiences in banking.

The AI Engineer will focus on building AI experiences, deploying models, and enhancing data workflows, working on greenfield applications. Key responsibilities include feature development, architecture collaboration, and shipping impactful product experiences.

The Director of Data Science leads data science and ML strategies for Commerce Media, focusing on ad tech initiatives, model development, and cross-functional collaboration.

Lead MongoDB's internal data product portfolio, focusing on GTM, analytics, and self-serve data capabilities while managing a team of Product Managers.

As a Data Scientist, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Manage AI engineering teams and client relationships, drive project deliverables, mentor staff, and uphold quality standards while leveraging advanced technologies.

The role involves managing client needs through technology solutions, mentoring team members, analyzing complex problems, and using AI/GenAI to enhance productivity and client relationships.

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

The Member of Technical Staff will focus on deploying advanced AI research in finance, building production-grade applications, mentoring teams, and driving innovation and collaboration across engineering efforts.

The Director of Developer Relations leads the strategy for engaging developers around CoreWeave's AI SaaS offerings, creating content, fostering community, and improving the onboarding experience.

The Senior Scientist II will lead AI-driven projects in oncology, developing agentic frameworks and predictive models while collaborating with teams and pharma partners.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Manage a team of ML engineers to build and optimize Affirm's economic decisioning engine using advanced ML techniques. Collaborate across teams, provide technical leadership, and mentor engineers while driving a cohesive long-term ML strategy.

The Head of AI and Data Transformation will lead BlackRock's AI and data strategies, enhancing product capabilities and driving innovative growth across the organization.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.