Azure MLOps Lead: Scale ML Pipelines & Deployments

EPAM Systems Inc; Colombia; Remote; COP 120,000,000 - 210,000,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Upskilling and certification courses

LinkedIn Learning access

Global career opportunities

Volunteering opportunities

Job summary

EPAM Systems Inc is seeking a seasoned Lead Microsoft Azure MLOps Engineer to join our team. You will lead the design and delivery of production-grade ML pipelines on Azure, collaborating with researchers and engineers to scale AI across projects.

The role requires hands-on expertise in Azure ML workloads, Kubernetes, Terraform, and CI/CD with Azure DevOps, along with strong Python skills and a track record mentoring engineers. You will drive reliability and modern MLOps practices.

Qualifications

• 5+ years delivering production ML systems and deployments
• 1+ years of technical leadership mentoring engineers
• Hands-on Azure ML workloads experience
• Strong Python with PyTorch and/or TensorFlow
• Strong CI/CD, testing, automation practices
• IaC with Terraform
• Fluent English (B2+)

Responsibilities

• Lead end-to-end MLOps pipelines for training and deployment
• Build CI/CD workflows for ML services and artifacts using Azure DevOps
• Deploy and operate ML workloads on Azure and Kubernetes
• Implement model lifecycle management, monitoring and alerting
• Mentor engineers and guide technical decisions
• Coordinate cross-functional teams to meet reliability and release goals
• Optimize infrastructure automation and reproducibility with Terraform
• Troubleshoot production issues across platform, pipeline, and runtime layers

Skills

MLOps

Azure

Kubernetes

Python

PyTorch

TensorFlow

CI/CD

Terraform

Model lifecycle

Tools

Azure DevOps

Kubernetes

Terraform

Job description

EPAM Systems Inc is seeking a seasoned Lead Microsoft Azure MLOps Engineer to join our team. You will lead the design and delivery of production-grade ML pipelines on Azure, collaborating with researchers and engineers to scale AI across projects.

The role requires hands-on expertise in Azure ML workloads, Kubernetes, Terraform, and CI/CD with Azure DevOps, along with strong Python skills and a track record mentoring engineers. You will drive reliability and modern MLOps practices.