M/L Ops Engineer

HD Supply • Atlanta, GA

4d • Onsite

About The Position

Transform machine learning models into stable, production-grade services by creating automated build and deployment pipelines, deploying containerized inference services, and configuring orchestration workflows. Define service benchmarks, implement drift and quality checks, and maintain secure configurations to ensure consistent and efficient performance at scale.

Requirements

• Bachelor’s degree in computer science, engineering, or a related field.
• 3+ years of experience in machine learning operations, DevOps, or machine learning platform engineering with direct experience in pipeline development and model deployment.

Nice To Haves

• Master’s degree in a related field.
• 2-4 years of experience in a related field.

Responsibilities

• Implements versioning, monitoring, and rollback mechanisms across the machine learning lifecycle.
• Partners with machine learning engineers to establish scalable, reliable integrations and service level agreements.
• Configures dashboards and alerts to continuously track model performance, data drift, and overall system health.
• Automates job scheduling, canary releases, and other operational tasks using workflow management tools.
• Manages the deployment of containerized microservices on Kubernetes and other cloud-native platforms.
• Maintains comprehensive documentation, including deployment playbooks and incident response procedures.
• Participates in incident response and root cause analysis to drive continuous system improvement.
• Contributes to engineering standards that promote collaboration, system resilience, and customer impact.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level