Quality Assurance Engineer

Is it Onsite/Remote/Hybrid: Hybrid

Quality Assurance Engineer

• Develop comprehensive test plans and strategies that cover functional, non-functional, and regression testing for ML models and MLOps pipelines.
• Define test cases for different scenarios, edge cases, and boundary conditions.
• Perform functional testing to verify that all features and workflows meet requirements.
• Conduct non-functional testing, including performance, scalability, and security testing in collaboration with the Security and Compliance team.
• Define and track quality metrics like defect density, test coverage, and mean time to detect (MTTD).
• Create automated test suites for model validation, including unit tests and integration tests.
• Design and execute performance tests to ensure models meet scalability requirements
• Implement data validation checks to maintain data quality throughout the ML lifecycle.
• Collaborate with the ML Engineer to define and track quality metrics for models in production.
• Develop and maintain documentation for testing procedures and quality standards.
• Participate in code reviews to ensure adherence to best practices and coding standards.

Experience:

• ML models: 3 years (Preferred)
• MLOps pipelines: 3 years (Preferred)
• unit tests: 3 years (Preferred)
• integration tests: 3 years (Preferred)
• Quality Assurance Engineer: 7 years (Preferred)

Language:

• Dutch (Preferred)