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AI Ethics Research Lead

Nexus Future Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join Nexus Future Labs at the forefront of ethical AI development as we shape the responsible technology landscape of 2026. As our AI Ethics Research Lead, you'll pioneer frameworks for bias mitigation, transparency, and human-centered AI in high-stakes environments. This role combines cutting-edge research with real-world implementation, ensuring our innovations align with evolving global standards. Collaborate with interdisciplinary teams to translate ethical principles into actionable engineering practices while publishing groundbreaking research in top-tier venues. Lead initiatives that influence industry best practices and contribute to the development of next-generation AI governance tools.

Responsibilities

  • Develop and implement ethical AI evaluation frameworks for autonomous systems
  • Lead cross-functional teams in bias detection and algorithmic fairness initiatives
  • Conduct original research on AI alignment and value learning mechanisms
  • Design transparency protocols for explainable AI (XAI) deployment
  • Advise product teams on ethical risk assessment and mitigation strategies
  • Author white papers and contribute to industry standards bodies
  • Manage research partnerships with academic institutions and policy organizations

Qualifications

  • PhD in Computer Science, Philosophy, Ethics, or related field with 5+ years AI research experience
  • Proven expertise in algorithmic bias detection and fairness metrics
  • Strong publication record in top-tier AI ethics/conference venues
  • Deep understanding of global AI regulatory frameworks (EU AI Act, NIST RMF)
  • Experience leading technical teams in ethical AI implementation
  • Expertise in value alignment and reinforcement learning safety techniques
  • Exceptional communication skills for translating complex ethical concepts

Required Skills

AI Ethics Algorithmic Fairness Explainable AI Machine Learning Governance Research Leadership Value Alignment Regulatory Compliance Risk Assessment

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