Lead DevOps/MLOps Engineer

EPAM Systems; United States; A distancia; USD 140.000 - 190.000; Jornada completa

Descripción de la vacante

EPAM Systems is seeking a Lead DevOps/MLOps Engineer to assess client infrastructure for deploying an Enterprise Data Platform. You will evaluate existing systems, identify gaps, and prepare scalable deployment strategies for data components.

You will collaborate with data engineering and DevOps teams to automate deployments on Kubernetes and ensure reliable ML workloads. Required: 5+ years in DevOps/MLOps, Docker, Kubernetes, Linux, CI/CD, Argo, Python, and strong English (B2+).

Formación

• 5+ years of DevOps/MLOps experience in data engineering environments.
• Experience assessing client infrastructure for data platform deployments.
• Familiarity with EDP components and deployment requirements.
• Ability to analyze complex environments and plan integration.

Responsabilidades

• Assess client infrastructure for EDP rollout feasibility.
• Identify gaps and remediation actions.
• Collaborate with data engineering and DevOps teams.
• Develop deployment automation scripts and tools.
• Coordinate with vendors for compatibility and support.
• Monitor performance and optimize deployments.
• Support continuous improvement of deployment processes.
• Deploy workloads on Kubernetes.

Conocimientos

DevOps

MLOps

Kubernetes

Docker

Linux

CI/CD

Argo

Python

Production ML

English B2+

Herramientas

MLflow

Airflow

ArgoCD

Descripción del empleo

We are seeking a driven and highly skilled Lead DevOps/MLOps Engineer to assess client infrastructure to enable the deployment of Enterprise Data Platform (EDP) components, aiming to ensure seamless integration and operational efficiency for a leading oil and gas company. The focus is on evaluating existing systems and preparing them for a scalable data platform rollout.

Responsibilities

• Conduct comprehensive assessments of client infrastructure for EDP rollout feasibility
• Identify and document infrastructure gaps and recommend remediation actions
• Collaborate with data engineering and DevOps teams to align deployment strategies
• Develop and maintain deployment automation scripts and tools
• Coordinate with third-party vendors to ensure compatibility and support
• Monitor infrastructure performance and provide feedback for optimization
• Support continuous improvement of deployment processes and infrastructure standards
• Deploy platform and application workloads on Kubernetes

Requirements

• 5+ years of experience in DevOps practices tailored to data engineering environments
• Expertise in infrastructure assessment and readiness evaluation for data platform deployments
• Knowledge of EDP components and their deployment requirements
• Ability to analyze complex client environments and identify potential integration challenges
• Experience collaborating within cross-functional teams and coordinating with external vendors
• Proficiency in Docker, Kubernetes, and Linux
• Skills in CI/CD, Argo, and Python
• Understanding of machine learning and agentic AI applications, and what it takes to deploy and run them reliably in production
• English proficiency at B2 level or higher

Nice to have

• Background in MLflow and Airflow
• Knowledge of automated retraining tools
• Exposure to data quality and monitoring tools