We are looking for a highly skilled MLOps Engineer to design, build, and manage end‑to‑end machine learning pipelines and production‑grade ML infrastructure. This role focuses on scalable ML deployment, monitoring, automation, and lifecycle management, while bridging the gap between Data Science, Engineering, and DevOps teams.

If you have strong expertise in ML model deployment, CI/CD for ML, cloud platforms, and Kubernetes, this is an excellent opportunity to work on enterprise‑scale AI/ML systems.

Key Responsibilities-

• Design, build, and maintain CI/CD pipelines for machine learning models and data pipelines

Automate model training, validation, testing, deployment, and rollback

• Deploy ML models as REST APIs / microservices in production environments

Implement model monitoring, data drift detection, and performance tracking

• Manage and optimize cloud infrastructure (AWS / Azure / GCP) for scal...