Top AI Ethics Jobs in San Francisco Bay Area, CA

Analyze generative AI content infringements and develop adversarial prompts to identify model vulnerabilities across hate speech, misinformation, intellectual property, and other abuse areas. Manage multilingual datasets, investigate safety circumvention tactics, oversee projects and quality assurance, and collaborate with engineering, product, and policy teams to improve AI safety strategies.

Lead development and evolution of youth-facing AI safety standards: synthesize expert and stakeholder input, document public standards, translate standards into testable evaluation rubrics, ensure transparency/versioning, and manage multi-track standards projects while coordinating with technical evaluators and leadership.

Convert interpretability research into production product features: design and build full-stack interfaces, APIs, workflows, and integrations for model evaluation, debugging, monitoring, and deployment. Partner with researchers, engineers, designers, and customers to deliver reliable, performant, and user-friendly tooling for understanding model internals.

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.

Design and operationalize enterprise AI governance capabilities across the AI lifecycle. Translate policies, privacy, security, risk, and compliance requirements into technical controls, guardrails, automated workflows, monitoring, observability, and audit evidence. Develop AI use-case registration, classification, taxonomy, risk assessment, and shadow-AI management capabilities. Partner with Privacy, Legal, Cybersecurity, Supply Chain, and Enterprise Architecture teams to implement responsible, secure, and compliant AI systems.

Lead design and implementation of AI and data governance frameworks, privacy guardrails, metadata standards, and compliance with GDPR/HIPAA/CCPA/NIST AI RMF. Monitor and audit models for bias, explainability, and transparency; partner with engineers, stewards, and leaders to embed ethical decision-making, set KPIs, run audits, and produce dashboards and reports to drive governance adoption.

Evaluate and improve AI-generated outputs for accuracy, clarity, quality, and business alignment. Develop and refine prompts, annotate data, conduct rubric-based assessments, fact-check content, and provide actionable feedback on model performance. Create and edit technical documentation, strategy reports, market analyses, business cases, executive summaries, and professional communications. The role requires strong analytical reasoning, writing, research, quality assurance, and attention to detail.

Develops and maintains AI governance policies, frameworks, and controls aligned with regulatory and industry standards. Conducts AI model risk assessments covering bias, explainability, data quality, and security; evaluates organizational and vendor risks; supports audits; designs controls; and partners with Legal, Privacy, Security, and Technology teams. The role also promotes compliant AI practices and organizational awareness while applying advanced AI/ML knowledge.

Lead strategy and execution for agentic AI product experiences across the DFIR portfolio. Define roadmaps, ship reliable and governed agentic features, drive adoption and growth, instrument metrics and experiments, run continuous discovery, and collaborate cross-functionally to ensure trustworthy, scalable AI-native products.