MLOps Engineer — LLMOps & AI Infra for Enterprise (Hybrid)

EPAM Systems; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

EPAM Employee Stock Purchase Plan (ES"

Job summary

EPAM Systems in London is seeking an experienced MLOps Engineer to join our hybrid team. You will build, deploy and maintain production-ready ML solutions, focusing on CI/CD, model serving, monitoring and scalable cloud infrastructure.

You will collaborate with engineering and data science teams, engage with clients on AI infrastructure best practices, and help extend capabilities toward LLMOps, RAG, and agentic AI workflows for enterprise environments.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering or related discipline.
• Experience delivering machine learning or MLOps systems into production environments.
• Proficiency in Python for building services, APIs, scripts and CI/CD automation.
• Working knowledge of modern MLOps stacks including experiment tracking and artifact management.
• Hands-on experience with orchestration tools (Kubeflow, Apache Airflow, Metaflow or Prefect).
• Demonstrated skills with Docker, Kubernetes and distributed deployments.
• Practical knowledge of Infrastructure-as-Code (Terraform) and a major cloud provider (AWS, Azure or GCP).
• Familiarity with ML model serving, scaling and monitoring frameworks in production.
• Strong communications skills to convey technical decisions and engage with clients effectively.

Responsibilities

• Build and maintain platform components for ML model training, deployment, serving and monitoring.
• Develop and optimize CI/CD pipelines for machine learning workflows.
• Implement and support model lifecycle management, including registries and observability tooling.
• Design and manage scalable, secure deployments using containerization and Kubernetes.
• Enable secure, reusable and automated workflows to enhance ML developer productivity.
• Extend platform capabilities to support LLMOps, RAG and agentic AI workloads.
• Collaborate with engineering teams to improve reliability, automation and operational maturity.
• Apply governance and compliance standards across AI operations.
• Participate in presales and client-facing sessions to translate requirements into scalable solutions.
• Advocate cloud best practices for reliability, scalability and cost optimization.

Skills

Python

CI/CD

MLOps

Docker

Kubernetes

Terraform

Airflow

Kubeflow

Metaflow

Prefect

Communication skills

Education

Bachelor’s or Master’s degree in Computer Science or Engineering

Tools

Kubeflow

Apache Airflow

Metaflow

Prefect

OpenTelemetry

Langfuse

Terraform

AWS

Azure

GCP

Job description

EPAM Systems in London is seeking an experienced MLOps Engineer to join our hybrid team. You will build, deploy and maintain production-ready ML solutions, focusing on CI/CD, model serving, monitoring and scalable cloud infrastructure.

You will collaborate with engineering and data science teams, engage with clients on AI infrastructure best practices, and help extend capabilities toward LLMOps, RAG, and agentic AI workflows for enterprise environments.