MLOps Engineer

EPAM Systems; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

EPAM Systems is seeking an MLOps Engineer to help transform systems to the cloud, optimize costs, and improve availability and analytics. You will focus on bringing ML models to production, maintaining them, and monitoring performance.

Responsibilities include managing ML lifecycle, framing problems from business objectives, designing data solutions, and deploying scalable ML pipelines using Vertex AI, Kubeflow, and related tools.

Qualifications

• 2+ years of experience in an MLOps or similar role.
• Proficiency in Python.
• Expertise in Google Vertex AI and Google Vertex AI Pipelines.
• Skills in monitoring ML models in production.
• Familiarity with Jenkins and Docker.
• English proficiency at B1+ level or above.

Responsibilities

• Understand and manage the ML systems lifecycle
• Frame ML problems based on business objectives
• Design data solutions tailored to the problem at hand
• Perform data preparation and processing
• Conduct model training and experimentation
• Build and automate ML pipelines
• Deploy models to the production system
• Monitor, optimize, and maintain models in production

Skills

Python

MLOps

Model monitoring

Vertex AI

Vertex AI Pipelines

English B1+

Tools

Jenkins

Docker

Kubeflow

Kubernetes

Groovy

JetBrains PyCharm

Ansible

Terraform

Google Cloud Platform

Job description

We are seeking an MLOps Engineer to join a major company that aggregates broad and deep property data and generates analytics informing smart decision-making and property-level insights relied upon by hundreds of thousands of users in the real estate industry.

In this role, you will help transform systems to the cloud, enabling cost optimization, improved availability and reliability through architectural improvements, and enhanced analytics with better TTM.

You will focus on streamlining the process of taking machine learning models to production, as well as maintaining and monitoring them.

Responsibilities

• Understand and manage the ML systems lifecycle
• Frame ML problems based on business objectives
• Design data solutions tailored to the problem at hand
• Perform data preparation and processing
• Conduct model training and experimentation
• Build and automate ML pipelines
• Deploy models to the production system
• Monitor, optimize, and maintain models in production

Requirements

• 2+ years of experience in an MLOps or similar role
• Proficiency in Python
• Expertise in Google Vertex AI and Google Vertex AI Pipelines
• Skills in monitoring ML models in production
• Familiarity with Jenkins and Docker
• English proficiency at B1+ level or above

Nice to have

• Background in AI Solution Engineering and Prompt Engineering
• Knowledge of Agentic SDKs and Google Agent Development Kit
• Experience with Google Cloud Platform, Ansible, and Terraform
• Familiarity with Kubeflow and Kubernetes
• Proficiency in Groovy and JetBrains PyCharm