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)
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