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Information Technology 🏢 Full Time ⭐️ Verified

AI Ethics Researcher

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
14 Mei 2026
Deadline
14 Mei 2027

Job Description

Join Nexus Future Labs at the forefront of ethical AI innovation. As an AI Ethics Researcher, you'll shape the responsible deployment of artificial intelligence in 2026 and beyond. Our interdisciplinary team combines cutting-edge technology with profound ethical insights to build systems that advance humanity while safeguarding human dignity. This role offers unparalleled opportunity to influence global AI governance frameworks and pioneer solutions to the most pressing ethical challenges of our digital future.

Responsibilities

  • Develop and implement ethical frameworks for AI systems in healthcare, finance, and autonomous technologies
  • Lead cross-functional research initiatives on algorithmic bias mitigation and fairness
  • Collaborate with policy experts to shape industry standards and regulatory compliance
  • Design predictive models for long-term societal impacts of advanced AI deployments
  • Author white papers and present findings at global ethics and technology conferences
  • Mentor junior researchers on responsible innovation methodologies
  • Partner with engineering teams to embed ethical safeguards into AI development pipelines

Qualifications

  • PhD in Ethics, Philosophy, Computer Science, or related field with AI specialization
  • 3+ years researching algorithmic bias, fairness, or AI governance frameworks
  • Published work in top-tier ethics/AI journals (e.g., Nature Machine Intelligence)
  • Expertise in regulatory landscapes (EU AI Act, NIST AI RMF)
  • Strong background in quantitative research methods and statistical analysis
  • Experience with interdisciplinary collaboration (tech, policy, humanities)
  • Exceptional communication skills for translating complex concepts to diverse stakeholders

Required Skills

AI Ethics Algorithmic Fairness Policy Development Research Methodology Governance Frameworks Bias Mitigation Predictive Modeling Interdisciplinary Collaboration

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