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Tier-1 brand, metro location and mid-level role with moderate ML/QA specialization.
Specialized AI/ML quality assurance skills limit cross-industry transfer without ML-focused experience.
Explicit 5-year requirement and extensive mandatory ML/QA tech skills create strict shortlisting.
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Own end-to-end QA/QC for AI/ML data quality and model performance including data ingestion, transformation, validation, and post-deployment drift monitoring.
Develop, implement, and maintain automated testing frameworks for data and ML model validation integrated within CI/CD and MLOps pipelines.
Identify, log, and drive resolution of data and AI defects while ensuring compliance with data governance, privacy, security, and AI regulatory standards.
Bachelor’s degree in computer science, IT, software engineering, or related field (equivalent experience considered).
Minimum 5 years of relevant work experience in QA/QC with focus on AI/ML data and model testing.
Proficiency in Python or similar (C#, R) and automation frameworks for ML testing (e.g., PyTest).
Experience with data validation tools (e.g., Great Expectations), CI/CD tools (Azure, Jenkins), and knowledge of AI governance and ethical compliance.
Experienced in full lifecycle QA of AI/ML projects including data pipelines, model validation, and performance monitoring in agile environments.
Strong hands-on skills in automated testing development, root cause analysis, and defect tracking with understanding of ML metrics and bias/fairness evaluation.
Comfortable operating independently with strong communication skills to report quality status and collaborate with developers and stakeholders across technical and non-technical domains.