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Information Technology 🏢 Full Time ⭐️ Verified

2026 AI Ethics Engineer

Quantum Leap Systems
Austin
Estimated Salary
USD 145.000 – USD 185.000
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join Quantum Leap Systems at the forefront of responsible AI development. We're pioneering ethical frameworks for autonomous systems in 2026 and seek visionary engineers to shape the future of human-machine collaboration. This role combines cutting-edge AI research with rigorous ethical governance to build technology that advances society while safeguarding human values.

Our Austin hub operates at the intersection of innovation and integrity, offering competitive benefits, flexible work arrangements, and opportunities to present at global AI ethics summits. Help us define the responsible tech landscape for the next decade.

Responsibilities

  • Design and implement ethical validation protocols for generative AI systems
  • Develop bias mitigation algorithms for 2026-era autonomous decision engines
  • Conduct adversarial testing of AI systems for ethical vulnerability assessment
  • Collaborate with cross-functional teams to embed ethical principles throughout product lifecycles
  • Author compliance documentation for emerging AI regulatory frameworks
  • Lead workshops on responsible AI development practices
  • Monitor and audit deployed AI systems for ethical drift

Qualifications

  • Master's degree in Computer Science, AI Ethics, or related field
  • 5+ years experience developing or auditing machine learning systems
  • Deep understanding of EU AI Act, NIST RMF, and emerging global AI regulations
  • Proficiency in Python, TensorFlow, and ethical auditing tools
  • Published research in AI ethics or responsible AI development
  • Experience with federated learning and differential privacy techniques
  • Certification in AI governance (e.g., CEGAI, CSEP)
  • Portfolio demonstrating ethical AI projects with measurable impact

Required Skills

AI Ethics Machine Learning Python TensorFlow Regulatory Compliance Algorithmic Bias Mitigation Federated Learning NIST RMF EU AI Act

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