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AI Ethics Research Scientist

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join Nexus Future Labs at the forefront of ethical AI innovation. We're seeking a visionary AI Ethics Research Scientist to shape the responsible future of artificial intelligence. As a key member of our interdisciplinary team, you'll develop frameworks to mitigate algorithmic bias, ensure transparency in autonomous systems, and pioneer ethical standards for next-gen AI applications. This role offers unparalleled opportunities to publish groundbreaking research, collaborate with Fortune 500 partners, and influence global AI policy.

Our San Francisco campus features state-of-the-art labs, flexible workspaces, and a culture dedicated to technological humanism. Enjoy competitive compensation, comprehensive benefits, and the chance to solve humanity's most pressing challenges through ethical AI.

Responsibilities

  • Design and implement bias detection protocols for machine learning models
  • Develop ethical frameworks for generative AI and autonomous systems
  • Conduct interdisciplinary research with sociologists, philosophers, and engineers
  • Partner with product teams to embed ethical safeguards into AI deployment
  • Author white papers and peer-reviewed publications on AI ethics
  • Advise policymakers on emerging AI governance challenges
  • Mentor junior researchers in ethical AI methodologies

Qualifications

  • PhD in Computer Science, Philosophy, Ethics, or related field (or equivalent experience)
  • 5+ years researching algorithmic bias or AI ethics
  • Expertise in fairness metrics and explainable AI techniques
  • Published work in top-tier AI ethics conferences (e.g., FAccT, NeurIPS Ethics Track)
  • Experience with large language model governance frameworks
  • Strong background in causal inference or causal modeling
  • Excellent communication skills for technical and non-technical audiences
  • Portfolio demonstrating ethical AI implementation projects

Required Skills

AI Ethics Machine Learning Algorithmic Bias Explainable AI Causal Inference Generative AI AI Governance Research Methodology

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