Ml Evaluation Engineer

Qualification: Bachelor's or Master's degree (16 years of education) in Computer Science, Artificial Intelligence, Data Science or a related field from an HEC-recognized university. Preference would be given to foreign qualified candidates with proven track record. Experience: At least 5 years in machine-learning engineering or ML testing and evaluation, including production model deployment or quality assurance. Skills & Competencies: • Python and ML frameworks (PyTorch / TensorFlow / scikit-learn) • Model evaluation, red-teaming and benchmark design • Bias, fairness and robustness testing methods • MLOps, experiment tracking and monitoring tooling • Clear technical reporting for non-specialist reviewers Key Performance Indicators (KPIs): • Share of production models passing standardized evaluation before deployment (target 100 percent). • Post-deployment issues detected through monitoring and time-to-remediation.