MLOps Engineer

About the role

The MLOps Engineer at Teknosys is a core technical role that bridges machine learning, DevOps, and software engineering. You will design, automate, and maintain the infrastructure that enables AI/ML models to be deployed, monitored, and operated reliably at scale.

Key responsibilities

• Design, build, and maintain CI/CD pipelines for machine‑learning models and AI applications.
• Automate the end‑to‑end ML lifecycle, including training, validation, deployment, and retraining workflows.
• Implement model monitoring to track performance, drift, and reliability in production.
• Manage model versioning, registries, reproducibility, and rollback strategies.
• Build and maintain scalable infrastructure for ML workloads using cloud platforms and containerization.
• Collaborate with data scientists and AI engineers to operationalize models and resolve deployment challenges.
• Apply infrastructure‑as‑code and configuration‑management practices to ML environments.
• Contribute to responsible and ethical AI practices, including data privacy, security, and governance.

Required profile

• Bachelor's or Master's degree in Computer Science, Software Engineering, AI, or a related field.
• 4+ years of experience in MLOps, DevOps, data engineering, or ML infrastructure.
• Strong problem‑solving, automation, and communication skills.

Required skills

• Python programming (and familiarity with Bash or similar scripting languages).
• CI/CD tools and ML pipeline frameworks such as MLflow, Kubeflow, Airflow.
• Cloud platforms: AWS, Azure, GCP.
• Containerization and orchestration: Docker, Kubernetes.
• Infrastructure‑as‑code tools: Terraform, Ansible.
• Version control systems (e.g., Git).
• Model monitoring, logging, and observability tools.

What we offer

• Opportunity to work at the forefront of Pakistan's digital transformation.
• Collaborative environment focused on continuous improvement and responsible AI.