AI Tester / AI Quality Assurance Engineer (Noida)

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 - Solid 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 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 - Solid 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