Mlops / Llmops Engineer

Qualification: Bachelor's or Master's degree (16 years of education) in Computer Science, Software Engineering, IT or a related field from an HEC-recognized university. Preference would be given to foreign qualified candidates with proven track record. Experience: At least 4 years of DevOps/MLOps experience with production ML systems. Skills & Competencies: • Docker/Kubernetes, CI/CD tooling (GitHub Actions, GitLab CI, Jenkins) • MLOps platforms (MLflow, Weights & Biases, Kubeflow, or equivalents) • Cloud infrastructure (AWS/Azure/GCP) and infrastructure-as-code • Monitoring and observability tooling • Scripting (Python/Bash) and Git Key Performance Indicators (KPIs): • Deployment frequency and lead time for AI model/application releases. • System reliability and incident-resolution time for production AI systems.