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

Lead hands-on research and engineering across agentic ML: train and fine-tune models, design evaluation and observability, build production improvement loops and tooling, prototype agent architectures, partner cross-functionally to productionize research, and set technical direction while mentoring senior engineers and scientists.

Own and scale Scale's coding AI product portfolio: set strategy and roadmap for benchmarks, training data, RL environments and evaluations; coordinate ML, engineering, operations and GTM; manage contributor networks, governance, contamination prevention, infrastructure, and customer engagements to convert benchmark credibility into revenue.

Lead architecture and technical direction for Scale's Generative AI Data Engine, embedding into high-priority Contributor teams to unblock delivery, overhaul platform infrastructure for LLM-native workloads, ensure scalability/reliability, mentor engineers, partner with product/leadership, and own large end-to-end backend, frontend, and ML system initiatives.

Manage end-to-end growth recruiting program: design and run top-of-funnel campaigns, optimize funnel conversion, own ATS (Greenhouse) and reporting, maintain hiring data integrity, lead recruiting operations improvements, and support hiring/onboarding from the San Francisco office.

Source, screen, and engage high-volume candidates to meet hiring goals; support candidates through the recruiting lifecycle; partner with recruiting and cross-functional leaders to design and execute sourcing strategies; manage evolving processes and represent the brand at occasional onsite recruiting events.

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

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.

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