MLOps Platform Engineer

EPAM Systems; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

EPAM Systems is seeking an MLOps Platform Engineer to help transform systems to the cloud, optimize costs, and improve availability for analytics in real estate data applications.

The role focuses on end-to-end ML lifecycle support, data solution development, model training and deployment, and post-deployment monitoring to ensure robust production systems.

Qualifications

• Experience building ML platforms and data pipelines.
• Proficiency in Python for ML workloads.
• Experience or familiarity with Vertex AI and pipelines.

Responsibilities

• Understand the ML systems lifecycle to support end-to-end delivery.
• Frame ML problems from business objectives.
• Develop data solutions tailored to business and technical requirements.
• Handle data preparation and processing for model readiness.
• Lead model training and experimentation efforts.
• Build and automate ML pipelines.
• Deploy models to the production system.
• Monitor, optimize, and maintain models post-deployment.

Skills

Python

ML monitoring

Cloud infrastructure

Tools

Google Vertex AI

Vertex AI Pipelines

Terraform

Jenkins

GCP

Job description

We are seeking an MLOps Platform Engineer to work with a major company that aggregates broad and deep property data and generates analytics that inform smart decision-making and property-level insights for hundreds of thousands of users in the real estate industry. This role will help transform systems to the cloud, enabling cost optimization, improved availability and reliability through architectural improvements, and enhanced analytics and TTM.

Responsibilities

• Understand the ML systems lifecycle to support end-to-end delivery
• Frame ML problems from business objectives
• Develop data solutions tailored to business and technical requirements
• Handle data preparation and processing for model readiness
• Lead model training and experimentation efforts
• Build and automate ML pipelines
• Deploy models to the production system
• Monitor, optimize, and maintain models post-deployment

Requirements

• 2+ years of experience as a Cloud Infrastructure Engineer or similar role
• Proficiency in Python
• Expertise in Google Vertex AI and Google Vertex AI Pipelines
• Familiarity with Terraform and Jenkins
• Background in monitoring ML models
• Knowledge of GCP is preferable
• English proficiency at B2 level or higher