AI Product Development Tester

Job highlights

• Education: Bachelors or masters degree in engineering,Computer Science,or a related field.
• Proficiency in SQL,Jupyter Notebook,Git,and CI / CD pipelines (Jenkins / GitHub Actions) is essential to enable robust and scalable testing
• A strong foundation in software testing principles,along with expertise in AI / ML testing,is required
• Experience: 3 - 5 years

AI Product Development Tester

Role: AI Product Development Tester
Location: Kolkata
Experience: 3 - 5 years
Education: Bachelor's or master's degree in engineering, Computer Science, or a related field.
Number of Positions: 2

Essential Skills

• AI/ML Testing Knowledge
• Data Validation Testing
• Proficiency in automation using Python/Java
• SQL Data Handling
• Understanding of performance testing tools (JMeter, Locust) especially for AI systems handling large-scale data.

Key Responsibilities

We are seeking a detail-oriented AI Product Development Tester (QA Engineer - AI/ML) to ensure the quality, reliability, and performance of AI-driven products through comprehensive functional, system, and model validation.

The role involves testing end-to-end AI workflows, validating machine learning models for accuracy, precision, recall, consistency, bias, and fairness, and ensuring data quality across both training and inference pipelines. The candidate will design and implement automation frameworks using Java and Python, leveraging tools such as PyTest, Selenium/Playwright, and Postman/REST Assured. Proficiency in SQL, Jupyter Notebook, Git, and CI/CD pipelines (Jenkins/GitHub Actions) is essential to enable robust and scalable testing.

A strong foundation in software testing principles, along with expertise in AI/ML testing, is required. This includes model validation techniques, data preprocessing checks, explainability, and handling data drift. The role also encompasses performance, scalability, and security testing of AI systems, ensuring compliance with data privacy standards and resilience against adversarial inputs.

Working closely with data scientists, ML engineers, and product teams, the candidate will validate monitoring and observability mechanisms and drive continuous quality improvement.

SPOC: Human Resources
Mail to: [email protected]