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Information Technology 🏢 Full Time ⭐️ Verified

AI Ethics Lead Engineer

NeuraTech Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join NeuraTech Dynamics at the forefront of responsible AI innovation. We're seeking an AI Ethics Lead Engineer to shape the ethical frameworks for our 2026-generation autonomous systems. This hybrid role combines cutting-edge technical expertise with philosophical rigor to ensure our AI solutions align with human values and regulatory standards. You'll collaborate with cross-functional teams to embed ethical safeguards into machine learning pipelines while pioneering industry best practices for transparent, accountable AI.

Our ideal candidate thrives at the intersection of technology and ethics, possesses deep knowledge of AI governance frameworks, and is passionate about democratizing AI responsibly. Enjoy competitive benefits, unlimited PTO, and the opportunity to define the future of ethical AI.

Responsibilities

  • Design and implement ethical governance frameworks for autonomous decision systems
  • Conduct bias audits and fairness assessments across ML pipelines
  • Develop algorithmic transparency protocols for regulatory compliance
  • Lead cross-functional ethics reviews for high-stakes AI deployments
  • Create audit trails for AI decision-making processes
  • Advocate for ethical AI principles in product development cycles
  • Establish industry benchmarks for AI accountability standards

Qualifications

  • MS/PhD in Computer Science, Philosophy, or related field
  • 5+ years in AI development with proven ethics integration experience
  • Expertise in fairness-aware ML and bias mitigation techniques
  • Deep understanding of EU AI Act, NIST AI RMF, and global AI regulations
  • Strong background in explainable AI (XAI) methodologies
  • Published research in AI ethics or responsible AI preferred
  • Certification in AI governance (e.g., CAG, AIE) required

Required Skills

AI Ethics Machine Learning Governance Bias Mitigation Explainable AI Regulatory Compliance Algorithmic Transparency Ethical Framework Design NIST AI RMF EU AI Act

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