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AI Ethics Research Lead 2026

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
13 Mei 2026
Deadline
13 Mei 2027

Job Description

Join Nexus Innovations at the forefront of ethical AI development as we shape responsible technology for 2026. We seek a visionary AI Ethics Research Lead to design governance frameworks that balance innovation with human-centric values. This pivotal role bridges technical teams, policymakers, and global communities to ensure AI systems align with societal needs while driving breakthroughs in machine learning and automation.

As a key architect of our 2026 AI roadmap, you'll pioneer methodologies for bias mitigation, transparent decision-making, and sustainable AI deployment. Our dynamic startup environment offers unparalleled opportunities to influence industry standards while working alongside Nobel laureates and Silicon Valley pioneers.

Responsibilities

  • Develop and implement ethical AI governance frameworks for 2026 technology deployments
  • Lead cross-functional research initiatives on algorithmic fairness and explainable AI
  • Collaborate with policymakers to shape emerging AI legislation and industry standards
  • Design bias detection tools and mitigation strategies for autonomous systems
  • Present findings at global tech summits and publish in peer-reviewed journals
  • Mentor interdisciplinary teams in ethical technology design principles

Qualifications

  • PhD in AI Ethics, Computer Science, Philosophy, or related field (or equivalent experience)
  • 5+ years researching AI governance or responsible technology frameworks
  • Published work in top-tier AI ethics conferences (e.g., FAccT, NeurIPS Ethics)
  • Expertise in bias auditing, fairness metrics, and transparency protocols
  • Experience collaborating with regulatory bodies (e.g., NIST, EU AI Act)
  • Proficiency in Python and statistical analysis tools for bias detection
  • Exceptional communication skills for technical and non-technical stakeholders

Required Skills

AI Ethics Machine Learning Governance Algorithmic Fairness Explainable AI Policy Development Bias Mitigation Statistical Analysis Python

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