Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

The Senior Software Engineer will drive the development of agent-powered data products, handling end-to-end product areas from frontend to backend, focusing on AI and intelligent workflows.

As a Forward Deployed AI Engineering Manager, you will integrate AI with enterprise clients, lead a team to deploy solutions, and ensure successful AI adoption.

Lead the design and operation of scalable backend systems for data generation and delivery, focusing on architecture, reliability, and integration with AI technologies.

The Senior Full-Stack Engineer will develop and scale web applications, manage frontend and backend operations, and work with AI systems and databases to enhance product experiences.

The AI Product Manager will lead technical partnerships and build data strategies to advance AI model development, requiring a strong entrepreneurial mindset and software engineering background.

As a Software Engineer for the ARC team, you'll design and implement secure backend systems, manage model inference layers, improve engineering standards, and collaborate with teams to meet government agency needs.

The role involves developing data solutions, collaborating with customers, and applying rigorous data science to affect business outcomes. Responsibilities include designing and deploying data solutions, conducting experiments, and influencing product strategy.

As a Software Engineer in Frontier AI Infrastructure, you'll design secure systems for the public sector, improve engineering standards, and collaborate with cross-functional teams to meet government requirements. You'll also participate in customer engagements and contribute to the product strategy while ensuring compliance with federal regulations.

Lead a portfolio of robotics data programs: coordinate cross-functional teams, design scalable data ingestion pipelines, manage robotic hardware and logistics, enforce data quality and governance, standardize SOPs, and deliver SQL-driven dashboards and executive updates to enable high-fidelity datasets for VLA models.

Lead the development of evaluation methodologies for large language models, collaborating with teams and publishing research findings. Enforce best practices in AI development.