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Information Technology 🏢 Full Time ⭐️ Verified

AI Ethics Research Lead

Nexus Labs
Austin
Estimated Salary
USD 185.000 – USD 250.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join Nexus Labs at the forefront of ethical AI development as we shape the technological landscape of 2026. We're seeking an AI Ethics Research Lead to pioneer responsible innovation in machine learning systems. This role combines cutting-edge research with real-world implementation to ensure AI advancements align with human values and societal benefit.

You'll collaborate with cross-functional teams to develop ethical frameworks, audit AI models for bias, and create industry standards that will define the next generation of intelligent systems. If you're passionate about ensuring technology serves humanity, this is your opportunity to make a lasting impact.

Responsibilities

  • Design and implement ethical frameworks for AI/ML systems development
  • Lead bias audits and fairness assessments of machine learning models
  • Develop industry standards for responsible AI deployment in 2026 tech ecosystems
  • Collaborate with engineering teams to integrate ethical safeguards into product lifecycles
  • Conduct research on emerging AI risks and mitigation strategies
  • Present findings to executive stakeholders and industry forums
  • Mentor junior researchers in ethical AI methodologies

Qualifications

  • PhD in Computer Science, Ethics, Philosophy, or related field
  • 5+ years of experience in AI ethics, algorithmic auditing, or responsible tech
  • Published research in top-tier AI ethics conferences (e.g., FAccT, NeurIPS Ethics Workshop)
  • Expertise in bias detection tools and fairness metrics (e.g., AIF360, IBM Fairness 360)
  • Deep understanding of global AI regulations (EU AI Act, NIST RMF)
  • Experience with MLOps pipelines and model deployment in production environments
  • Exceptional communication skills for translating complex ethics concepts to technical teams

Required Skills

AI Ethics Machine Learning Algorithmic Auditing Bias Detection MLOps Regulatory Compliance Research Methodology

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