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Qa Lead – Ai/Ml Systems

India, Pune · Job Posted June 03, 2026
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Job Description

We are looking for an experienced QA Lead – AI Systems to lead the validation and quality assurance of AI-powered products, including LLM/RAG systems, Software as a Medical Device (SaMD), and other AI-driven digital solutions. This is a key leadership role responsible for establishing end-to-end QA frameworks, validation strategies, and compliance processes for AI/ML models across development and deployment pipelines. The ideal candidate will bridge data science, software engineering, and regulatory QA to ensure AI systems meet performance, safety, and compliance standards.

Job Responsibility

  • Own and drive QA strategy for AI systems across the model, data, and product lifecycle
  • Lead AI model validation efforts, covering LLM/RAG testing, bias analysis, and performance evaluation
  • Define and implement AI Evaluation Metrics (accuracy, fairness, drift, explainability) aligned with business and regulatory expectations
  • Establish frameworks for Explainability Testing (SHAP, LIME, XAI) and ensure interpretability of AI outcomes
  • Collaborate with Data Science and MLOps teams to validate models within cloud environments (Azure ML, AWS Sagemaker, Vertex AI)
  • Drive verification and validation (V&V) for AI models and applications under FDA and SaMD compliance frameworks
  • Ensure test traceability, documentation, and audit readiness in line with ISO 13485, IEC 62304, and ISO 14971
  • Develop Python-based automation for AI testing, data validation, and model evaluation pipelines
  • Provide technical leadership to QA teams, ensuring alignment with AI/ML development best practices
  • Collaborate with cross-functional teams (Product, Data, Regulatory, Engineering) to identify risks, gaps, and opportunities for test optimization
  • Present validation findings, risks, and recommendations to senior stakeholders and regulatory reviewers

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Biomedical Engineering, or related field
  • 8–12 years of total QA experience, with 2–3 years directly in AI/ML or GenAI QA
  • Proven experience in AI Model Validation, LLM/RAG Testing, and AI Evaluation Metrics
  • Strong knowledge of MLOps concepts and cloud platforms (Azure ML, AWS Sagemaker, Vertex AI)
  • Understanding of FDA AI/ML Compliance, SaMD testing, and regulated software QA
  • Hands-on expertise in Python automation and testing AI/ML pipelines
  • Excellent documentation and communication skills with ability to produce traceable validation artifacts

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