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Metro location, mid-level experience and broad SDET title increase applicant competition.
Specialized ML/LLM testing skills limit easy cross-industry transferability.
Explicit 5–8 years, required ML testing expertise and Python make hiring filters strict.
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Own end-to-end quality assurance for ML models, AI agents, and AI-powered features within Automotive Retail Cloud.
Design and implement automated testing and evaluation frameworks for non-deterministic AI model outputs including hallucination detection and consistency checks.
Utilize AI/LLMs to generate test cases, synthetic data, and automation scaffolding to enhance test coverage and speed, and drive root cause analysis and quality monitoring.
5–8 years experience in SDET, quality engineering, or software engineering with test automation framework development.
Strong programming skills in Python and/or Java, capable of writing production-quality automation code.
Hands-on experience testing data-intensive or ML/AI systems or strong software testing background with demonstrated ML/LLM knowledge.
Solid understanding of ML concepts (model training, inference, evaluation metrics) and LLM/agent concepts including prompting, RAG, embeddings, and familiarity with generative failure modes.
Experience working closely with ML engineers, data scientists, and product teams in a high-scale SaaS or data platform environment.
Demonstrated ability to design and execute evaluation strategies for AI/LLM-based features involving automated scoring and evaluation datasets.
Strong analytical and debugging skills focused on model, data, and code layers with a strategic focus on preventing production issues via quality metrics and monitoring.