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

Own and build People programs including compensation strategy, leveling and career pathways, performance management, learning & development, retention measurement, and org design. Partner with founders and finance to model comp/headcount tradeoffs, instrument programs as products, and iterate using data for an AI-native workforce.

Manage and deliver high‑impact dataset and data‑solution projects for frontier AI labs. Scope, coordinate expert contributors, design dataset specifications, write production Python code, and drive projects end‑to‑end to influence foundation model training and product outcomes.

Manage end-to-end interview scheduling and candidate logistics, maintain ATS records, coordinate interviewers and feedback, support recruiting operations, and improve hiring workflows and documentation to deliver a high-touch candidate experience.

Own full-cycle technical recruiting for engineering and applied-AI roles: source, screen, coordinate interviews, manage offers, and build recruiting systems, pipelines, and metrics while partnering directly with founders and hiring managers.

Design and build full‑stack data capture workflows (Next.js web, Python desktop), architect high‑throughput data pipelines with low latency, collaborate on product strategy, ship features rapidly, and establish engineering best practices for team growth.

Identify and engage research teams at frontier AI labs through outbound prospecting and events, qualify leads, maintain CRM hygiene, and partner with founders to build ICPs, messaging, and outbound sales playbooks to convert outreach into qualified pipeline.

Design, build, and own core infrastructure for large-scale data generation, evaluation, and human-in-the-loop systems. Architect distributed, high-throughput pipelines, shared developer platforms, and reliable production services. Ensure scalability, observability, and fault tolerance while collaborating with research and engineering teams to support AI experimentation and platform capabilities.

Lead client-facing, end-to-end strategic projects with frontier AI labs: scope, design dataset specifications, coordinate expert cross-functional teams, drive delivery and revenue, and support high-impact operational initiatives across engineering, AI, and business functions.

Partner with the CEO and operations team to run special projects end-to-end, build operational capabilities (billing, revenue ops, BD support), gather and analyze qualitative and quantitative data, support recruiting and administrative finance/office functions, identify and fix operational inefficiencies, and document and hand off durable processes.

Design datasets, evaluation rubrics, and reward signals for RLHF/RLVR; build real and synthetic data pipelines; run experiments modeling annotator behavior; develop quantitative metrics for dataset quality, diversity, and downstream impact; partner with research teams to translate training objectives into data and evaluation specs.