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Information Technology 🏢 Full Time ⭐️ Verified

AI Ethics Researcher

InnovateForward Labs
San Francisco
Estimated Salary
USD 140.000 – USD 200.000
Live Update
13 Mei 2026
Deadline
13 Mei 2027

Job Description

Join InnovateForward Labs at the forefront of responsible AI development. We're seeking an AI Ethics Researcher to shape the future of artificial intelligence while ensuring ethical frameworks guide our innovations. This role bridges cutting-edge technology with human-centric values, driving solutions that balance progress with privacy, fairness, and societal impact.

In this pivotal position, you'll collaborate with cross-disciplinary teams to audit AI systems, develop ethical guidelines, and pioneer transparent methodologies. Our culture values intellectual curiosity, collaborative innovation, and a commitment to technology that serves humanity. Enjoy competitive benefits, flexible work arrangements, and the opportunity to influence global AI standards.

Responsibilities

  • Design and implement ethical frameworks for AI model development and deployment
  • Conduct bias audits and fairness assessments across AI systems
  • Develop governance protocols for responsible AI lifecycle management
  • Lead stakeholder workshops on AI ethics and transparency best practices
  • Research emerging regulatory landscapes and advise on compliance strategies
  • Author white papers and industry standards for responsible AI adoption
  • Mentor junior researchers on ethical technology principles

Qualifications

  • PhD or Master's in Computer Science, Ethics, Philosophy, or related field
  • 3+ years researching AI ethics, algorithmic bias, or responsible AI
  • Expertise in regulatory frameworks (EU AI Act, NIST AI RMF)
  • Strong background in machine learning model evaluation
  • Experience with qualitative/quantitative research methodologies
  • Exceptional communication skills for technical and non-technical audiences
  • Published work in AI ethics or technology ethics conferences/journals

Required Skills

AI Ethics Machine Learning Governance Regulatory Compliance Bias Detection Research Methodology Stakeholder Engagement

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