MLOps Engineer

We at Verdantas are seeking an experienced and innovative AI DevOps Engineer to support the deployment, scaling, and monitoring of AI / ML models and infrastructure. This role bridges the gap between data science and operations, ensuring that machine learning workflows are automated, reproducible, and production ready.

Key Responsibilities

• Design and maintain CI / CD pipelines for AI / ML model training, testing, and deployment.
• Automate infrastructure provisioning using Infrastructure as Code (IaC) tools like Terraform or CloudFormation.
• Manage containerized environments using Docker and Kubernetes, including GPU orchestration.
• Collaborate with data scientists to productionize ML models using MLOps best practices.
• Monitor model performance and system health using tools like Prometheus, Grafana, or ELK Stack.
• Implement model versioning, experiment tracking, and reproducibility using tools like MLflow, DVC, or Kubeflow.
• Ensure security, compliance, and scalability of AI workloads on cloud platforms (AWS, Azure, GCP).
• Optimize compute resource usage and cost for training and inference workloads.

Required Skills & Qualifications :

Preferred Qualifications :

Location and Work Set-up