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Ethical AI Specialist

2 weeks ago

Lucknow, Uttar Pradesh, India beBeeResponsible Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Job Title: Responsible AI Specialist

We are seeking a highly skilled and principled expert to assess, audit, and ensure the ethical development and deployment of AI 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.

  • 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).
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.
Preferred Qualifications:
  • Master's or PhD in Computer Science, Data Science, Ethics, or related field.
  • Prior work with model evaluation benchmarks and large-scale LLM testing frameworks.
  • Knowledge of secure and privacy-preserving ML techniques (e.g., federated learning, homomorphic encryption).