Top AI Ethics Jobs in San Francisco Bay Area, CA

Lead UX research to define and scale evaluation of Notion's AI experiences. Create reusable rubrics and measurement approaches, run longitudinal and feature-specific studies, identify failure modes and recovery behaviors, and operationalize evaluation with product, design, engineering, and data science partners to improve model output quality and end-to-end user experience.

Design and deliver custom AI-driven legal workflows, implement and scale post-sales solutions, define KPIs and success metrics, inform product strategy, partner with Customer Success to demonstrate ROI, and maintain objective, ethics-compliant processes and playbooks for plaintiff law firms.

Lead strategy and architecture for the enterprise knowledge/context layer powering AI: set standards, control models, connector strategy, and federated operating models. Ensure content is AI-ready, permissions-aware, and measurable for retrieval and grounding. Partner with IT, Engineering, Legal, Privacy, and Security to define eligibility, sensitivity, and lifecycle policies and drive adoption across domains.

Design, train, and evaluate Responsible AI components: fine-tune LLMs (including RLHF), build adversarial agent evaluations and safety mitigations, collaborate with engineering to deploy mitigations at scale, monitor operational performance, and troubleshoot end-to-end issues.

Develop and deploy responsible AI solutions that identify, measure, and mitigate bias across Pinterest’s large-scale machine learning applications, including generative AI, search, and recommendation systems. Collaborate with trust and safety, user modeling, content understanding, and engineering teams to adopt fairness tooling and practices. Mentor engineers, contribute to technical strategy, and bridge advanced research with product impact.

Leads applied AI risk standards for areas including mental health, youth safety, age assurance, reliability, efficacy, and privacy. Translates research, policies, and evaluation methods into measurable standards, test methods, assessment criteria, and assurance requirements. The role involves drafting proposals, negotiating with standards bodies, coordinating internal stakeholders, representing OpenAI externally, and contributing to frontier AI risk-management and independent-assessment standards.

Leads responsible AI adoption across eDiscovery and litigation support, translating strategy into defensible workflows, measurable efficiency, and cost control. Manages AI pilots, governance, workflow redesign, training, vendor relationships, and adoption metrics. Oversees eDiscovery advisors and subject matter experts while advising attorneys, clients, leadership, and technology teams on legal technology, AI governance, data privacy, and complex cross-border matters.

Own the strategy, design, development, and deployment of AI safeguards systems and product experiences across Anthropic’s products and cloud platforms. Define safety-by-design approaches, develop evaluations and risk metrics, prioritize roadmaps, make technical tradeoffs, and collaborate with policy, research, engineering, enforcement, and product stakeholders to mitigate deployment and user risks.

Leads development and delivery of a technical course focused on AI safety, likely coordinating curriculum, instructors, learners, and course operations.

Lead and build Thinking Machines’ product policy function, establishing usage, content, safety, model release, and developer-facing policies. Hire and manage a team, create product and model risk review frameworks, develop decision-making infrastructure, and partner with Research, Product, Trust & Safety, Communications, Public Policy, and Legal. Translate complex AI policy questions into actionable executive recommendations and responsible launch mitigations.