Job Description
Join Nexus AI Labs at the forefront of shaping ethical AI frameworks for 2026. We're seeking an AI Ethics Research Lead to pioneer responsible innovation in generative AI systems. You'll collaborate with cross-functional teams to develop governance protocols, bias mitigation strategies, and transparency standards that will define the next generation of artificial intelligence. This role offers unparalleled opportunity to influence industry-wide ethical standards while working with cutting-edge AI technologies.
Our ideal candidate thrives at the intersection of technology and philosophy, combining deep technical expertise with strong ethical reasoning. You'll be instrumental in creating audit frameworks for autonomous systems and advising product teams on ethical implementation. This is a leadership position with direct impact on our company's AI roadmap and industry best practices.
Responsibilities
- Design and implement ethical governance frameworks for generative AI systems
- Lead bias audits and fairness assessments for machine learning models
- Develop transparency protocols for AI decision-making processes
- Collaborate with engineering teams to embed ethical safeguards into AI pipelines
- Advise product teams on ethical implementation of AI features
- Conduct research on emerging AI ethics challenges and regulatory trends
- Create educational materials for stakeholders on responsible AI practices
- Represent the company in industry ethics consortiums and regulatory discussions
Qualifications
- PhD or Master's in Computer Science, Ethics, Philosophy, or related field
- 5+ years of experience in AI ethics, algorithmic fairness, or responsible AI
- Expertise in bias detection and mitigation techniques for ML systems
- Strong understanding of global AI regulations (EU AI Act, NIST frameworks)
- Published research in AI ethics or related academic journals
- Experience developing corporate AI ethics policies and audit protocols
- Exceptional communication skills for technical and non-technical audiences
- Proficiency in Python for bias analysis and model auditing