REMOTE MLOps Engineer

We are seeking an experienced Senior MLOps Engineer to support a high-impact initiative focused on modernizing machine learning infrastructure. This role will play a critical part in migrating existing machine learning pipelines to a modern Kubeflow-based architecture, helping accelerate the adoption of scalable, production-ready MLOps practices.

The ideal candidate will bridge the gap between data science and engineering, ensuring machine learning workflows are reliable, maintainable, and optimized for production. This is a hands-on role for someone who enjoys building infrastructure, improving development practices, and enabling data scientists to move faster.

About the Team

The E-Commerce MLOps team provides machine learning engineers and data scientists with a fully featured platform for research, development, and deployment of ML solutions.

This initiative is focused on accelerating workload migrations and achieving key platform goals before year-end.

What You’ll Do

• Analyze and document data input/output requirements for existing ML pipelines

• Break down existing workflows into modular, self-contained pipeline components

• Migrate machine learning pipelines to a Kubeflow-based platform

• Develop and maintain containerized solutions using Docker and Kubernetes

• Follow Test-Driven Development (TDD) methodologies to ensure code quality and reliability

• Leverage AI-assisted development tools such as Codex, Claude, and Windsurf to increase productivity

• Build, test, and validate end-to-end prototypes locally before deploying to production environments

• Collaborate closely with machine learning engineers, data scientists, and platform teams

• Contribute to CI/CD processes, automation, and deployment best practices

• Help establish scalable engineering standards for machine learning operations

5+ years of experience in Software Engineering, DevOps, MLOps, or a related field

• Experience delivering and supporting production-grade software systems

• Strong proficiency in Python, SQL, Pandas

• Hands-on experience with Docker, Kubernetes (self-hosted environments preferred)

• Git and modern version control workflows, CI/CD pipelines and deployment automation

• Strong command-line (CLI) proficiency

• Experience gathering technical requirements and translating them into implementation plans

• Demonstrated experience with Test-Driven Development (TDD)

• Ability to independently develop and run end-to-end prototypes in a local containerized environment - Golang

• Bash scripting

• Experience with Kubeflow

• Experience using AI-powered development tools for coding and software delivery