Senior Azure MLOps Engineer

EPAM Systems; Colombia; Remote; COP 150,000,000 - 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

Job summary

EPAM Systems Inc. seeks a Senior Azure MLOps Engineer to design production-grade ML pipelines on Azure and Kubernetes, collaborating with researchers, data scientists, and engineers to deliver scalable AI solutions.

You will build CI/CD workflows for model packaging and deployment, implement monitoring and incident response, automate testing, and maintain infrastructure as code for reproducible environments across global projects.

Qualifications

• 3+ years of experience deploying ML models to production environments
• Hands-on experience with Microsoft Azure for ML workloads
• Strong Python skills with PyTorch and/or TensorFlow

Responsibilities

• Design production-grade MLOps pipelines for training, deployment, and monitoring
• Build CI/CD workflows for model packaging, validation, and rollout
• Deploy ML and foundation models on Microsoft Azure and Kubernetes platforms
• Implement model lifecycle management across versioning and promotion stages
• Develop monitoring and alerting for model performance and service health
• Automate testing and quality gates for ML code and pipelines

Job description

We are seeking a Senior Azure MLOps Engineer to join our team and help deploy and operate ML and foundation models reliably in production on cloud infrastructure. You will collaborate with researchers, data scientists, and engineers to build robust pipelines, automation, and monitoring. Apply to help shape scalable AI delivery!ResponsibilitiesDesign production-grade MLOps pipelines for training, deployment, and monitoringBuild CI/CD workflows for model packaging, validation, and rolloutDeploy ML and foundation models on Microsoft Azure and Kubernetes platformsImplement model lifecycle management practices across versioning and promotion stagesDevelop monitoring and alerting for model performance, drift, and service healthAutomate testing and quality gates for ML code and pipelinesCollaborate with data scientists and researchers to operationalize experimentsOptimize ML deployment performance and reliability for production workloadsCoordinate cross-functional delivery with platform and engineering teamsMaintain infrastructure as code to enable reproducible environmentsTroubleshoot production issues across pipelines, services, and runtime dependenciesRequirements3+ years of experience deploying ML models to production environmentsHands-on experience with Microsoft Azure for ML workloadsStrong experience building MLOps pipelines with CI/CD and model lifecycle managementProduction project experience operating ML services with monitoring and incident response practicesStrong Python skills with PyTorch and/or TensorFlow expertiseStrong software engineering skills in testing, code quality, and automationStrong collaboration skills working with ML researchers and cross-functional teamsAzure DevOps experience supporting CI/CD workflowsTerraform experience managing infrastructure as codeUpper-Intermediate English level (B2)Nice to haveAzure Kubernetes Service (AKS) experience running ML workloadsDatabricks experience supporting ML pipelines or feature workflowsGoogle Cloud Platform experience with ML services or infrastructureWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedInEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.