
AI Ethics Specialist
6 days ago
We are seeking a highly skilled and principled AI Ethics Specialist to assess, audit, and ensure the ethical development and deployment of Artificial Intelligence Models across the enterprise.
This role spans traditional Machine Learning models, Large Language Models (LLMs), and Generative AI Systems, with a strong focus on fairness, transparency, privacy, security, and accountability across multi-cloud environments (AWS, Azure, GCP, etc.).
The ideal candidate combines deep technical expertise with a firm grasp of Ethical Frameworks, regulatory requirements, and responsible AI principles.
Key Responsibilities:
- Model Evaluation & Auditing
- Evaluate AI/ML, LLM, and GenAI models for bias, fairness, explainability, and robustness.
- Conduct red-teaming, safety testing, and adversarial analysis across AI pipelines.
- Perform pre-deployment, post-deployment, and continuous model audits.
- Operationalize and implement RAI principles based on NIST AI RMF, OECD, ISO/IEC 42001, and industry standards.
- Collaborate with data scientists, legal, compliance, and product teams to enforce responsible AI lifecycle checkpoints.
- Ensure AI/ML systems deployed across AWS, Azure, GCP, and hybrid environments meet data residency, compliance, and ethical standards.
- Evaluate model behavior variability and risk exposure across different cloud providers.
- Build or integrate tools for model explainability (e.g., SHAP, LIME), fairness (AIF360, Fairlearn), and privacy (DP libraries).
- Leverage LLM-specific eval frameworks (e.g., TruthfulQA, HELM, RAGAS, model-card generators).
- Produce model cards, system cards, and impact assessments (e.g., DSA, DPIA).
- Deliver detailed evaluation reports, risk scores, and mitigation recommendations for internal and external stakeholders.
Required Skills and Qualifications:
- 5+ years of experience in AI/ML evaluation, testing, or assurance roles.
- Proven experience with LLMs (e.g., GPT, Claude, LLaMA) and generative AI (e.g., DALL·E, Midjourney, custom diffusion models).
- Strong knowledge of fairness, bias detection, differential privacy, red-teaming, model transparency techniques.
- Familiarity with AI regulation and governance (EU AI Act, FTC guidance, DSA, HIPAA, etc.).
- Experience with cloud platforms (AWS, Azure, GCP) and deploying/evaluating AI services in distributed architectures.
- Proficiency in Python and libraries such as scikit-learn, Transformers, LangChain, MLflow, PyTorch, etc.
- Strong communication and reporting skills, with the ability to translate technical findings into business risk language.
Benefits:
- Work at the cutting edge of AI ethics, safety, and trust.
- Collaborate with interdisciplinary teams across engineering, legal, and policy.
- Influence how AI is responsibly used across industries and sectors.
- Shape a safer and more accountable AI future.
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