Top AI Ethics Jobs in San Francisco Bay Area, CA

The CTO will lead Fathom's technical strategy, focusing on AI governance, building partnerships, defining standards, and advancing AI safety practices.

Lead enterprise AI strategy, governance, and adoption. Establish AI policies and responsible-AI practices, prioritize business use cases, align AI investments with organizational goals, and drive measurable business value from AI solutions across the company.

Lead the Agent & Reinforcement Learning Environments data vertical, owning roadmap, data-as-product, pipelines, tooling, and evaluation frameworks. Partner with AI research teams and customers to scope and scale RL environments, drive cross-functional execution across engineering, operations, and go-to-market teams, and translate research needs into product outcomes.

The Technical Governance Researcher will conduct research and writing on AI governance, policy, and safety, engaging with collaborators and policymakers to address existential risks from AI.

As a Research Engineer, you will tackle AI safety challenges, develop evaluation methodologies, conduct adversarial testing, and work on model alignment and interpretability. You'll bridge theoretical and practical applications of AI safety research and collaborate with product teams to implement safety solutions.

As a Technical Product Intern, you'll prototype user safety features, conduct competitive analysis, and translate compliance frameworks into product logic, focused on real-time AI enforcement.

Evaluate AI outputs, perform audit-based reviews, identify failure modes and trends, apply and refine guidelines, communicate findings, participate in calibrations and stakeholder syncs, and help improve evaluation frameworks for human-in-the-loop AI.

Leads trust and safety for AI products serving teachers and students. Owns model guardrails, evaluations, red-teaming, monitoring, incident response, student-facing safety, district trust documentation, and regulatory alignment. Builds safety infrastructure into product development, manages incidents and postmortems, partners with Legal and Engineering, and leads a growing Trust & Safety team.

Lead enterprise AI adoption by developing rollout plans, training programs, workflow playbooks, automation use cases, tool governance, acceptable-use policies, and risk controls. Measure adoption and business outcomes, manage an AI champions network, supervise a team, and partner with Security, Legal, Compliance, IT, Procurement, Product, and Engineering. The role focuses on safe, practical AI use across healthcare operations while addressing PHI, retention, vendor data use, HIPAA, and SOC 2 requirements.

Leads enterprise knowledge and AI transformation across Customer Success, Support, Enablement, Product, Operations, and Technology. Develops knowledge architecture, taxonomy, governance, metadata, content standards, ownership, and lifecycle processes. Builds AI-ready knowledge foundations for retrieval, self-service, copilots, and agentic workflows. Evaluates and implements AI opportunities, improves content and response quality using performance data, drives Knowledge-Centered Service practices, and leads cross-functional adoption and change without direct authority.