Lead QA Engineer

At this time, we are unable to offer visa sponsorship for this position(H1b/OPT). Candidates must be legally authorized to work for any employer in the United States (or (applicable country) on a full-time basis without the need for current or future immigration sponsorship QA Engineer (AI/ML) (Exempt) Enterprise AI/ML Organization Reports to Leader of ML Engineering Group OVERVIEW This QA Engineer position is for a hands-on professional with experience in testing and automating AI/ML pipelines. The ideal candidate is someone who has worked closely with machine learning engineers and data scientists to ensure the quality and reliability of AI/ML models and systems. You will join a dynamic team passionate about innovation, learning, and applying cutting-edge technologies to deliver high-quality AI solutions. RESPONSIBILITIES • Develop and implement QA strategies tailored for AI/ML solutions, including models, APIs, pipelines, and agent-based architectures. • Create and maintain automated and manual test cases for model validation (accuracy, bias, robustness, explainability, drift). • Collaborate with AI engineers, data scientists, and product teams to define success criteria, acceptance standards, and performance metrics. • Validate model outputs and system behaviors against business and ethical guidelines. • Perform regression, integration, stress, and adversarial testing of AI models and systems. • Identify, log, and track bugs and anomalies, ensuring timely resolutions. • Support monitoring production AI systems to detect model performance degradation (concept drift, data drift, hallucinations). • Ensure compliance with internal AI governance standards, responsible AI principles, and regulatory requirements. • Contribute to building automated AI testing frameworks, pipelines, and synthetic data generation systems. • Document testing procedures, results, and quality assessments clearly and effectively. Must Haves: • Bachelor’s degree in Computer Science, Engineering, or a related field. • Minimum 6 years of experience in quality assurance, specifically testing AI/ML applications. • Experience with the following: • Hands-on skills with Python and relevant AI/QA libraries (Pytest, Unittest, Great Expectations, MLflow, Deepchecks, etc.). • Familiarity with machine learning frameworks (TensorFlow, PyTorch, or scikit-learn). • Experience with test automation tools and frameworks. • Knowledge of CI/CD tools (Jenkins, GitLab CI, or similar). • Experience with containerization technologies like Docker and orchestration systems like Kubernetes. • Familiarity with version control systems like Git. • Strong understanding of software testing methodologies and best practices. • Excellent analytical and problem-solving skills. • Excellent communication and collaboration skills. #LI Apply tot his job