Quality Assurance Engineer

We are looking for an experienced AI Testing / AI QA Engineer to ensure the quality, reliability, and performance of AI/ML-based applications. The candidate will be responsible for validating AI models, testing data pipelines, and ensuring that AI systems perform accurately and reliably in production environments.

Key Responsibilities

Design and implement test strategies for AI/ML models and AI-driven applications.

Validate data quality, model accuracy, and performance metrics.

Develop and execute test cases for AI models, APIs, and data pipelines.

Perform functional, regression, and automation testing for AI applications.

Test model behavior, bias, fairness, and edge-case scenarios.

Work closely with data scientists, ML engineers, and development teams.

Identify, track, and resolve defects in AI models and automation workflows.

Validate AI model deployment and integration in production environments.

Required Skills

Strong experience in software testing and QA methodologies.

Knowledge of AI/ML concepts and model validation techniques.

Experience with Python, SQL, Pandas, and NumPy.

Experience with API testing tools such as Postman or REST Assured.

Hands-on experience with test automation tools like Selenium, Cypress, or Playwright.

AI / ML Tools & Technologies

AI frameworks: TensorFlow, PyTorch, Scikit-learn, Keras

AI testing & validation tools: Deepchecks, Evidently AI, Great Expectations

ML monitoring tools: WhyLabs / WhyLogs

MLOps tools: MLflow, Kubeflow

Containerization: Docker, Kubernetes

5+ years of experience in QA / software testing with exposure to AI/ML systems.

Education

Bachelors or Masters degree in Computer Science, IT, Data Science, or related field.