Number of Positions: 2 Education Qualification: B.E/B.Tech. /M.C.A./Graduate (IITs/NITs and BITS graduates preferred) Roles & Responsibilities Design and execute test strategies for AI/ML models, data pipelines, and AI-enabled applications Validate data quality, data drift, feature integrity, and training/validation datasets Test model accuracy, precision, recall, bias, fairness, and explainability Perform functional, integration, regression, and non-functional testing for AI systems Automate AI testing using Python, test frameworks, and MLOps pipelines Monitor model performance post-deployment and identify degradation or drift Validate AI outputs against business rules and real-world scenarios Collaborate with data scientists, ML engineers, and product teams Ensure compliance with AI governance, privacy, and regulatory standards Document test cases, test results, risks, and quality metrics Required Skills & Qualifications Strong understanding of Software Testing and QA processes Knowledge of Machine Learning concepts (supervised/unsupervised learning, NLP, CV basics) Experience with Python and data analysis libraries (Pandas, NumPy, Scikit-learn) Familiarity with AI testing techniques: bias testing, adversarial testing, model validation Experience with automation tools and CI/CD pipelines Understanding of data validation, data drift, and model monitoring Knowledge of API testing and cloud platforms (AWS, Azure, GCP) is a plus Strong analytical, problem-solving, and communication skills Preferred Experience Experience with MLOps tools Exposure to Responsible AI, explainability tools, and ethical AI practices Experience testing GenAI systems (LLMs, chatbots, prompt validation, hallucination checks) Apply Now