Top AI Ethics Jobs in San Francisco Bay Area, CA

Supports AI governance projects by assessing risks and controls, documenting processes, gathering requirements, analyzing information, and synthesizing findings. Advises clients on regulatory compliance, risk management, internal controls, and governance improvements. The role involves applying AI/ML governance frameworks such as NIST and ISO, translating technical concepts for stakeholders, collaborating with diverse teams, and developing expertise in corporate governance and risk management.

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.

Develop and execute enterprise AI and data strategies for clients, including AI value cases, operating models, talent strategies, technology roadmaps, responsible AI plans, and commercialization opportunities. Build trusted C-suite relationships, lead transformation workstreams, shape new business opportunities, and guide large-scale AI-enabled reinvention initiatives. The role requires consulting experience, strong program management and communication skills, leadership capability, and up to 80% travel.

Develop machine learning techniques focused on AI safety, alignment, and trustworthiness. Collaborate with product, research, and engineering teams to design, build, deploy, monitor, and iterate responsible AI systems at scale, from experimentation to production for large language models and distributed AI services.

Design and implement technical AI governance frameworks for generative and agentic AI systems. Assess ethical, safety, security, and sociotechnical risks; evaluate architectures, data flows, permissions, tool integrations, and human oversight; and develop practical mitigations and controls. Partner with engineering, product, legal, security, and business teams to embed responsible AI practices, conduct red teaming and risk assessments, support regulatory alignment, and advance AI literacy across the organization.

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.