Job Description
Join Nexus Horizons Institute at the forefront of shaping responsible AI for 2026. We're seeking a visionary AI Ethics Research Lead to architect ethical frameworks that will guide next-generation autonomous systems and human-AI collaboration. This pivotal role combines cutting-edge research with real-world policy impact, ensuring technological advancement aligns with humanity's best interests. You'll lead cross-disciplinary teams in developing preemptive governance models for AI deployment in healthcare, climate tech, and critical infrastructure.
Our 2026 Futures program partners with UN agencies, Fortune 50 innovators, and academic pioneers to create actionable ethics blueprints. This hybrid role offers 40% remote flexibility with quarterly in-person strategy retreats in our Palo Alto R&D campus. Compensation includes equity grants in our AI ethics incubator and professional development budgets for conference participation at venues like NeurIPS and ICML.
Responsibilities
- Design and implement preemptive AI ethics frameworks for 2026-era autonomous systems
- Lead cross-functional research teams in identifying ethical risks in emerging AI applications
- Develop policy recommendations for federal AI governance bodies and international standards bodies
- Conduct scenario planning for high-stakes AI-human interaction models in critical infrastructure
- Author white papers and ethical guidelines adopted by industry consortiums
- Mentor PhD fellows in AI ethics through our 2026 Futures fellowship program
- Collaborate with climate tech teams to ensure AI deployment aligns with sustainability targets
Qualifications
- PhD in AI Ethics, Philosophy of Technology, or related field with 5+ years applied research
- Proven track record of publishing in top-tier AI ethics journals (e.g., ACM FAccT, Nature Machine Intelligence)
- Expertise in EU AI Act, NIST RMF, and other emerging regulatory frameworks
- Experience leading multi-stakeholder ethics initiatives with Fortune 100 companies
- Strong background in value-sensitive design methodologies for autonomous systems
- Technical proficiency in Python and ML model auditing tools (e.g., IBM AI Fairness 360)
- Deep understanding of existential risk mitigation strategies in advanced AI development