Key Responsibilities :

- Design, build, and maintain automation frameworks to test AI/ML applications, models, and services.

- Automate validation of model predictions, accuracy, and performance using test datasets.

- Develop automated regression and functional tests for data pipelines, APIs, and ML workflows.

- Integrate automation tests with CI/CD pipelines for continuous validation.

- Collaborate with Data Science and Engineering teams to define test strategies, acceptance criteria, and edge cases.

- Implement scalable and reusable automation scripts to improve testing efficiency.

- Ensure data quality validation as part of the automation framework.

- Report defects, track issues, and provide clear documentation of automation coverage and results.

What Youll Need to Be Successful (Required Skills) :

- 3- 5 years of QA experience with at least 1+ years in automation for AI/ML applications.

- Strong programming skills in Python, Java, or JavaScript for test automation.

- Experience automating tests for ML workflows, APIs, and data pipelines.

- Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) for model validation.

- Hands-on experience with automation tools/frameworks (e.g., Selenium, PyTest, Robot Framework, Cypress).

- Solid understanding of CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps, or similar).

- Knowledge of testing

Education/ Certifications :

- Bachelors degree in computer science, Engineering, or a related field, or equivalent relevant experience.

Preferred Skills :

- Exposure to AI/ML testing challenges such as bias detection, explainability, and performance benchmarking.

- Experience with cloud platforms (AWS, Azure, GCP) for deploying and testing ML models.

- Familiarity with data validation frameworks and synthetic data generation for ML testing.

- Experience with containerization and orchestration tools (Docker, Kubernetes) for test environments.