Senior MLOps Platform Engineer

EPAM Systems; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

EPAM Systems is seeking a Senior MLOps Platform Engineer to help scale ML workloads, migrate systems to the cloud, and boost availability, cost efficiency, and time-to-market for real estate analytics used by a vast user base.

You will own end-to-end ML pipelines, drive training and deployment, and implement Vertex AI, Vertex AI Pipelines, Terraform, and Jenkins for scalable production systems.

Qualifications

• Minimum 3 years working as a Cloud Infrastructure Engineer or in a comparable position.
• Strong command of Python.
• Deep knowledge of Google Vertex AI and Google Vertex AI Pipelines.
• Experience working with Terraform and Jenkins.
• Prior exposure to ML model monitoring GCP knowledge is a plus B2-level English or above.

Responsibilities

• Grasp the ML systems lifecycle to enable complete end-to-end delivery
• Translate business goals into well-defined ML problems
• Create data solutions that align with both business and technical needs
• Manage data preparation and processing to get models ready
• Spearhead model training and experimentation initiatives
• Construct and automate ML pipelines
• Launch models into the production environment
• Track, fine-tune, and sustain models after deployment

Skills

Python

Cloud infrastructure

MLOps

Model deployment

English communication

Tools

Google Vertex AI

Vertex AI Pipelines

Terraform

Jenkins

Job description

We're looking for a Senior MLOps Platform Engineer to collaborate with a leading company that compiles comprehensive property data and produces analytics driving informed decisions and property insights for a vast user base in real estate. In this position, you'll contribute to migrating systems to the cloud, which will optimize costs, boost availability and reliability via architectural upgrades, and strengthen analytics and time-to-market.

Responsibilities

• Grasp the ML systems lifecycle to enable complete end-to-end delivery
• Translate business goals into well-defined ML problems
• Create data solutions that align with both business and technical needs
• Manage data preparation and processing to get models ready
• Spearhead model training and experimentation initiatives
• Construct and automate ML pipelines
• Launch models into the production environment
• Track, fine-tune, and sustain models after deployment

Requirements

• Minimum 3 years working as a Cloud Infrastructure Engineer or in a comparable position
• Strong command of Python
• Deep knowledge of Google Vertex AI and Google Vertex AI Pipelines
• Experience working with Terraform and Jenkins
• Prior exposure to ML model monitoring GCP knowledge is a plus B2-level English or above