Lead ML & MLOps Engineer for Production AI Systems

EPAM Systems Inc; United States; On-site; USD 120,000 - 190,000; Full time

Job summary

EPAM Systems Inc. is seeking an experienced Machine Learning / MLOps Engineer to bridge research and production systems. You will develop, fine-tune, deploy, and scale ML/models in production across Azure and AKS, focusing on robust MLOps infrastructure and high GPU utilization.

You will collaborate with ML researchers, data scientists, and cross-functional teams to translate breakthroughs into production-ready systems, emphasizing CI/CD, observability, and software engineering discipline.

Qualifications

• Hands-on production ML experience.
• Strong Python with PyTorch and/or TensorFlow.
• Experience building and operating MLOps pipelines.
• Experience deploying ML workloads on Azure and Kubernetes.
• Strong software engineering practices (testing, version control, automation).

Responsibilities

• Develop, fine-tune, and deploy ML and foundation models into production environments.
• Build, scale, and operate end-to-end MLOps pipelines, including CI/CD and model lifecycle management.
• Deploy and manage ML workloads on Azure and AKS with high availability and security.
• Optimize multi-GPU workloads for performance and resource utilization.
• Collaborate with ML researchers, data scientists, and engineers to translate research into production-ready systems.

Skills

Python

PyTorch

TensorFlow

MLOps

CI/CD

Cloud computing

Cross-functional teamwork

Tools

Azure

Kubernetes

CI/CD

Job description

EPAM Systems Inc. is seeking an experienced Machine Learning / MLOps Engineer to bridge research and production systems. You will develop, fine-tune, deploy, and scale ML/models in production across Azure and AKS, focusing on robust MLOps infrastructure and high GPU utilization.

You will collaborate with ML researchers, data scientists, and cross-functional teams to translate breakthroughs into production-ready systems, emphasizing CI/CD, observability, and software engineering discipline.