Senior ML Infrastructure Engineer (DevOps)

About the role

We are seeking a Senior ML Infrastructure Engineer with a strong DevOps focus to own the end‑to‑end production lifecycle of machine‑learning models serving millions of customers. You will work closely with applied scientists, turning prototypes into reliable, high‑performance services while participating in a 24×7 on‑call rotation.

Key responsibilities

• Monitor and maintain real‑time inference services, respond to alerts, debug incidents, perform rollbacks and write post‑mortems.
• Design, build and evolve AWS infrastructure using IaC, CI/CD pipelines, Kubernetes, Docker, autoscaling and cost‑control mechanisms.
• Manage the GPU fleet – driver and CUDA upgrades, node provisioning, capacity planning and troubleshooting.
• Automate user access, SSH keys, service accounts and developer environments for the science team.
• Run streaming data pipelines into an online feature store and serve low‑latency features.
• Orchestrate batch workloads with Apache Airflow or Databricks Workflows.
• Partner with scientists to productionise prototypes and ensure their long‑term health.
• Write and review production‑grade Python code, including AI‑generated snippets.

Required profile

• Proven experience in 24×7 on‑call rotations for high‑load online services, with live incident resolution.
• Strong Linux administration skills and hands‑on experience with Kubernetes, Docker and Infrastructure as Code.
• Solid Python programming, Git version control and CI/CD workflow expertise.
• Experience with workflow orchestration tools such as Apache Airflow or Databricks Workflows.
• Proficiency in AWS services and cost‑optimisation practices.
• English proficiency at B2 level or higher.

Required skills

• Python
• Linux
• Kubernetes
• Docker
• Infrastructure as Code (e.g., Terraform, CloudFormation)
• CI/CD pipelines
• Git
• AWS
• Apache Airflow
• Databricks Workflows
• NVIDIA driver / CUDA

What we offer

• Fully remote work from any location in Armenia.
• Access to EPAM’s internal learning platform and certification programs (GCP, Azure, AWS).
• Leadership development, career advising and well‑being programs.
• Opportunity to work abroad up to two months per year and relocation within EPAM’s global offices.
• Employee Stock Purchase Plan participation and monetary bonuses.
• Corporate and social events, free English classes with certified teachers.