Top AI & Machine Learning Jobs in San Francisco, CA

Lead design and development of core GenAI platform capabilities and scalable backend services to power multi-step AI workflows, model execution, and integrations. Build shared APIs/execution patterns, ensure reliability and extensibility, collaborate with AI engineers, data scientists, and product teams, and operationalize production-grade GenAI systems across the organization.

The Staff Machine Learning Engineer will lead AI product initiatives, optimize ML models for Edge devices, and work with petabyte-scale data, collaborating across teams to enhance customer operations.

Lead the design and evolution of Samsara's ML platform, collaborating across teams to build and operate scalable ML systems that improve safety outcomes.

Lead the technical direction for AI-powered, real-time in-vehicle experiences. Define product and architecture, build backend orchestration for edge clients, ensure reliability, safety, and observability, ship zero-to-one features, mentor firmware engineers, and integrate AI-assisted development tools.

Design, build, test, deploy, monitor, and maintain production LLM-based agentic solutions for Commercial Customer Success. Integrate agents with CRMs and Samsara systems, create evaluation frameworks and automated tests, own deployment/versioning/rollback, detect drift, and iterate to improve customer outcomes and retention.

Lead the Safety AI team in developing computer vision and machine learning solutions for AI dash cameras, ensuring safety insights through real-time data integration. Oversee model lifecycle and collaborate with engineering teams to deliver customer-focused AI products.

Design, train, optimize, and deploy computer vision and ML models at petabyte scale for video-based safety and telematics. Work on edge and backend inference, collaborate with cross-functional teams, and translate customer needs into production ML solutions.

Design, build, and operate production AI systems and marketing data infrastructure. Develop pipelines, CDP integrations, retrieval systems, and agent orchestration. Partner with BI and stakeholders to translate requirements, automate workflows, ensure data quality, ship Python/SQL solutions, mentor engineers, and evaluate LLMs in production.

Lead the design and implementation of Safety AI initiatives, developing real-time perception systems for edge devices, mentoring engineers, and leveraging cutting-edge computer vision techniques.

Lead the technical vision and architecture for AI-powered GTM systems, defining reference architectures and governance across low-code platforms and custom agentic pipelines. Architect and prototype high-complexity integrations, LLM orchestration, RAG systems, and event-driven backends. Partner with GTM leadership, perform architecture reviews, drive tool selection, and produce internal thought leadership to ensure scalable, auditable, and human-overseen AI systems.