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Information Technology 🏢 Full Time ⭐️ Verified

AI Ethics Strategist

Nexus Innovations Inc.
San Francisco
Estimated Salary
USD 150.000 – USD 200.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

Join Nexus Innovations Inc. at the forefront of responsible AI development as we shape the ethical framework for 2026 and beyond. We seek an AI Ethics Strategist to pioneer governance solutions that balance innovation with societal impact. This role offers unparalleled influence in designing AI systems that align with human values while driving business growth.

Our team operates at the intersection of technology and ethics, collaborating with Fortune 500 partners to develop cutting-edge AI applications. You'll work in our state-of-the-art San Francisco headquarters, with hybrid flexibility and comprehensive benefits including equity, wellness stipends, and professional development funds.

Responsibilities

  • Design and implement AI ethics frameworks for autonomous systems and predictive analytics
  • Conduct bias audits and risk assessments for machine learning models
  • Develop stakeholder engagement protocols for diverse community input
  • Lead cross-functional workshops on responsible AI deployment
  • Author whitepapers on emerging ethical challenges in generative AI
  • Advocate for regulatory compliance with evolving global standards
  • Mentor junior engineers on ethical coding practices

Qualifications

  • Master's degree in Ethics, Philosophy, Computer Science, or related field
  • 5+ years in AI governance or responsible tech implementation
  • Expertise in Fairness, Accountability, and Transparency (FAT) principles
  • Published work on algorithmic bias mitigation or AI ethics
  • Proficiency with regulatory frameworks (EU AI Act, NIST AI RMF)
  • Experience with model explainability tools (SHAP, LIME)
  • Strong background in stakeholder diplomacy and policy development

Required Skills

AI Ethics Machine Learning Governance Algorithmic Auditing Stakeholder Engagement Regulatory Compliance Model Explainability FAT Principles Policy Development

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