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Metro location and common Test Engineer title increase competition, balanced by AI/ML specialization and lesser-known employer.
Medium because ML-specific testing skills are transferable across industries but require ML familiarity and data-testing experience.
Moderate because technical filters require Python, PyTest, API testing and ML validation skills though no explicit years specified.
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Design and execute comprehensive test strategies and plans for AI/ML applications ensuring accuracy, reliability, performance, and scalability.
Validate AI/ML model outputs, data pipelines, and transformations against expected results and business requirements using appropriate performance metrics.
Develop and maintain automation test scripts using Python and frameworks like PyTest; perform functional, integration, regression, system, API, and end-to-end testing including REST API testing with tools like Postman.
Understanding of Machine Learning concepts and algorithms including supervised and unsupervised learning.
Experience in validating ML model predictions and outputs.
Proficiency in Python and test automation frameworks such as PyTest.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in testing AI/ML solutions with a focus on model validation and data pipeline verification.
Skilled in automation testing and API testing in AI/ML service environments.
Comfortable designing test strategies for complex ML-driven systems ensuring robustness and performance.