MLOps Engineer

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

Benefits

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn