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Information Technology 🏢 Full Time ⭐️ Verified

AI Ethics Research Scientist

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 240.000
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join Nexus Future Labs at the forefront of ethical AI development. As we pioneer technologies for 2026, we seek an AI Ethics Research Scientist to shape the future of responsible artificial intelligence. You'll collaborate with cross-functional teams to develop frameworks ensuring AI systems align with human values while driving innovation in quantum computing and neural networks.

Our San Francisco campus offers state-of-the-art labs and a culture dedicated to solving humanity's greatest challenges. This role reports directly to our Chief Ethics Officer and includes competitive equity packages.

Responsibilities

  • Design and implement ethical AI governance frameworks for 2026 technology stack
  • Conduct advanced research on bias mitigation in generative AI systems
  • Lead cross-functional ethics audits for autonomous decision-making algorithms
  • Develop real-time ethical monitoring systems for quantum AI applications
  • Author white papers on emerging AI ethics challenges and solutions
  • Advocate for ethical AI principles in industry standards development
  • Mentor junior researchers on responsible AI methodologies

Qualifications

  • PhD in Ethics, Philosophy, Computer Science, or related field (or equivalent experience)
  • 5+ years researching AI ethics with published papers in peer-reviewed journals
  • Expertise in machine learning fairness metrics and bias detection algorithms
  • Proficiency in Python and statistical analysis tools (R, TensorFlow)
  • Deep understanding of global AI regulatory landscapes (EU AI Act, US frameworks)
  • Experience working with quantum computing interfaces or neural network architectures
  • Exceptional communication skills for translating complex concepts to diverse stakeholders

Required Skills

AI Ethics Machine Learning Quantum Computing Bias Mitigation Governance Frameworks Regulatory Compliance Research Methodology Neural Networks

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