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

Join the Personalization-Memory team to research and implement long-horizon memory and personalization for frontier models. Own research agenda, build evaluations, design and debug code across the research stack, and collaborate with product and engineering to translate research into product impact.

Conduct multimodal safety research to ensure text, vision, and audio models behave safely. Build training and evaluation methods for VLMs, develop post-training interventions, design safety evaluations, diagnose failures, and collaborate with product and model teams to translate research into safer multimodal experiences.

Lead hands-on growth experiments across acquisition, activation, lifecycle, and early retention for SMB advertisers. Build campaigns, landing page and messaging tests, AI-assisted assets and automation, partner with cross-functional teams, maintain experiment documentation, and translate ideas into measurable tests to drive first meaningful spend and repeat value.

Lead and drive large-scale product and platform programs across ChatGPT, API, web, and mobile. Translate product vision into technical plans, manage timelines, dependencies, risks, and stakeholder alignment. Influence architecture and API interfaces, coordinate cross-functional teams, and use data/AI tooling to optimize delivery and developer experiences.

Lead applied data science for GTM and Technical Success: build predictive and causal models (propensity, churn, uplift), define customer health and metrics, create next-best-action systems embedded in workflows, measure intervention effectiveness, partner across Product/Engineering/RevOps/Sales, and hire and mentor a small data science team to drive adoption and expansion.

Build end-to-end AI-powered developer product experiences spanning frontend, backend, agent and prompt design, cloud infrastructure, and developer tooling; collaborate with product, design, and research; engage users to validate solutions; and improve reliability, scalability, and performance.

Lead product strategy for core AI models: define model requirements, build learning loops from product signals to training and evaluation, set success metrics balancing quality, safety, latency and cost, and partner with research, engineering, model design, and data science to move capabilities into the mainline model and launch stack.

Design, build, and scale privacy features and infrastructure using confidential computing, trusted execution environments, and end-to-end encryption across ChatGPT, the API, and future devices. Improve build systems, integrate safety and integrity tooling, operate highly reliable systems at scale (including on-call), and collaborate cross-functionally with product, security, safety, policy, and legal teams.

Build and operate developer-facing APIs and backend services for multimodal AI (image, audio, real-time). Design low-latency streaming, session, and model-integration systems; ensure availability, latency, scalability, and cost efficiency. Partner with Research, Inference, and Safety; own projects end-to-end from design through launch and iteration.

Manage cross-functional safety and risk processes for model deployments, track safety research and mitigations, run pre-launch safety reviews, build compute roadmaps, document metrics and evaluations, coordinate with partners (e.g., Microsoft), and publish safety learnings and datasets.