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Information Technology 🏢 Full Time ⭐️ Verified

AI Ethics Researcher - 2026 Vision

Nexus Futures
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Join Nexus Futures at the forefront of responsible AI development. As an AI Ethics Researcher for our 2026 Vision Initiative, you'll shape the future of human-machine collaboration by pioneering ethical frameworks for next-generation autonomous systems. Work with Nobel laureates and industry disruptors in our state-of-the-art Silicon Valley hub, where cutting-edge research meets real-world impact.

We're seeking visionary thinkers who can navigate complex ethical dilemmas while driving innovation. Your work will directly influence global AI governance policies and set new standards for human-centered technology.

Responsibilities

  • Develop comprehensive ethical frameworks for autonomous decision-making systems
  • Lead cross-functional workshops to align technical teams with ethical guidelines
  • Conduct bias audits and fairness assessments for AI models
  • Author white papers on AI governance for international policy forums
  • Collaborate with product teams to embed ethical safeguards into development lifecycle
  • Mentor junior researchers in emerging AI ethics methodologies
  • Present findings at global AI ethics conferences and summits

Qualifications

  • PhD in Philosophy, Computer Science, Cognitive Science, or related field
  • 3+ years researching AI ethics, algorithmic bias, or machine learning governance
  • Expertise in cross-cultural ethical frameworks and policy analysis
  • Published work in peer-reviewed journals or conference proceedings
  • Proficiency in Python and statistical analysis tools
  • Experience working with multinational regulatory bodies (e.g., EU AI Act, NIST frameworks)
  • Demonstrated ability to translate complex ethical concepts into actionable guidelines

Required Skills

AI Ethics Machine Learning Governance Cross-cultural Ethics Policy Analysis Python Statistical Modeling Regulatory Compliance Research Methodology

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