Responsible AI
2 weeks ago
About the Role:We are seeking a highly skilled and principled Responsible AI Evaluator to assess, audit, and ensure the ethical development and deployment of AI models across the enterprise. This role spans traditional ML 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 & AuditingEvaluate 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.Responsible AI FrameworksOperationalize 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.Multi-Cloud Deployment ComplianceEnsure 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.Tooling & AutomationBuild 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).Documentation & ReportingProduce 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 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).Experience contributing to open-source Responsible AI tools or policy frameworks.Why Join Us: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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