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

Lead end-to-end deployments of AI systems in semiconductor companies, focusing on integrating models with chip design and verification workflows. Responsibilities include designing production systems, delivering AI-powered workflows, and ensuring successful project outcomes.

The role involves designing and implementing safeguards to mitigate loss of control risks in advanced AI models, requiring collaboration and technical expertise.

The Recruiting Infrastructure Manager will manage OpenAI's recruiting technology ecosystem, including analytics, automation, vendor management, and data governance. Responsibilities involve leading a team, optimizing tools for better workflows, and ensuring data quality while driving operational efficiency and experience improvements.

As a Frontend Engineer, you'll develop user-facing identity experiences for secure access, collaborating with teams to design and implement identity flows like sign-in and account management.

Develop systems for 3D perception and tracking in robotics using SLAM and multi-view geometry, focusing on real-time and large-scale data processing.

Lead the development of AI personalization features for ChatGPT. Balance innovation, user privacy, and product vision through collaboration with cross-functional teams.

The Backend Software Engineer will design and build infrastructure for evaluating and enhancing OpenAI's support automation, collaborating with teams to develop pipelines and APIs.

An Operating Systems Engineer will develop and maintain OS components, focusing on security, performance, and reliability for consumer products, collaborating with various teams.

Incubate and build new platform capabilities from ambiguous customer signals: design, implement, pilot with design partners, debug in production, and transition scalable solutions to core teams while driving adoption, observability, and safety.

The Ops Lead will enhance operational systems within the Forward Deployed Engineering team, managing staffing, capacity planning, project prioritization, and execution tracking to scale AI deployment effectively.