Senior AI Test Engineer

AI Model Validation

• Design and implement comprehensive testing strategies to ensure the robustness, accuracy, and reliability of AI/ML models in production.
• Develop automated test scenarios to evaluate model performance, detect data drift, and identify algorithmic bias.
• Collaborate with Data Science and MLOps teams to integrate testing into CI/CD pipelines.

Data Quality & Integration Testing

• Validate the consistency, integrity, and traceability of datasets used for training and inference.
• Support the verification of data pipelines and the integration of models into cloud environments (Azure, AWS, GCP).

Automation & Monitoring

• Build automated testing tools for ML/AI models, including regression, performance, and robustness tests.
• Implement monitoring systems to detect anomalies and ensure model stability post-deployment.

Collaboration & Documentation

• Work closely with ML engineers, developers, and project managers to ensure the quality of AI deliverables.
• Document test plans, results, and continuous improvement recommendations.

Requirements

Technical Skills:

• Strong proficiency in Python and testing frameworks (e.g., PyTest, unittest).
• Familiarity with AI testing tools (e.g., DeepChecks, Great Expectations, MLflow).
• Experience with cloud platforms (Azure, AWS, GCP) and CI/CD tools (Git, Jenkins, GitLab CI).
• Solid understanding of ML/AI models and their potential vulnerabilities.

Experience:

• 6+ years in software or test engineering, with at least 3 years focused on AI/ML systems.
• Proven experience validating production-grade models and implementing automated test suites.