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Tier-1 brand, metro location, and mid-level generalist title create stacked applicant competition.
Test automation skills transfer across industries, though ML/EDA-specific testing raises moderate domain specificity.
Explicit 4–6 years, mandatory Python/CI/CD/test-framework skills and domain testing experience raise filter strictness.
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Develop and execute system integration and regression tests for ML R&D software projects involving AI agents and infrastructure.
Implement and maintain automated test frameworks and CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins) for validation and benchmarking.
Analyze test failures and benchmark regressions, collaborating with development teams to improve test coverage and software quality.
4+ years of professional experience in software engineering, system integration testing, or test automation.
Proficient in Python for test automation and development of testing infrastructure.
Experience with CI/CD tools and automated test workflows (e.g., GitHub Actions, GitLab CI, Jenkins).
Bachelor's degree in Computer Science, Engineering, or related field (MS or PhD with corresponding lower experience also accepted).
Experienced in designing and maintaining pytest-based automation frameworks and test containers for integration and system testing.
Familiar with benchmarking performance, scalability, and stability metrics in software systems, preferably ML or AI-driven.
Able to handle debugging and collaborate effectively with cross-functional engineering teams on root-cause analysis and quality improvement.