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

The Research Scientist will design evaluation measures for AI systems, collaborate with agencies, and publish research on AI risks.

As an Engagement Management Lead, you'll manage strategic customer relationships, oversee project delivery, and ensure quality outcomes while navigating complex customer dynamics.

Lead and scale a global ML Research organization focused on frontier generative AI, evaluation, agents, safety, and alignment. Set technical direction, translate research into production solutions, partner with GTM and Fortune 100 customers, manage senior research leaders, and drive cross-functional planning including budget and headcount.

Design, evaluate, and deploy production AI agents that combine LLMs, retrieval, memory, and traditional ML. Build retrieval and memory pipelines, multi-agent systems, evaluation frameworks, and production guardrails. Run experiments and ablation studies, collaborate with infrastructure and enterprise customers, and measure business impact while ensuring reliability, safety, and observability.

Design, evaluate, and deploy production AI agents combining LLMs, retrieval, memory, and tool use. Build retrieval/memory pipelines, multi-agent systems, evaluation frameworks, and production engineering for reliable, safe enterprise AI deployments while partnering directly with customers.

Design and implement end-to-end features across front-end, back-end, and infrastructure for Scale's Generative AI Data Engine. Build scalable systems using TypeScript, MongoDB, Elasticsearch, and Temporal that handle millions of tasks weekly. Own high-impact revenue-critical systems, collaborate with model and cross-functional teams, and help shape engineering culture and best practices on a hybrid team in San Francisco or New York City.

The Enterprise Account Executive will drive revenue growth in strategic enterprise accounts, manage relationships, and coordinate internal teams for successful sales processes.

Perform part-time quality audits and evaluations of task outputs, define and refine quality benchmarks and scoring rubrics, analyze audit results to produce actionable insights and reports, and recommend process improvements to raise output quality.