US|DevOps Engineer|Level II
Software Engineering
Remote
Posted on Aug 22, 2026
Our client is currently seeking a US|DevOps Engineer|Level II
We are seeking an experienced Senior MLOps Engineer to help lead a critical infrastructure initiative:
migrating existing ML pipelines to a modern KubeFlow architecture. In this role, you will bridge the gap between engineering and data science, ensuring that our machine learning production lifecycle is robust, scalable, and maintainable. You will be responsible for gathering data input/output requirements, break down the existing pipeline into self contained steps, and executing the migration following a Test-Driven Development (TDD) approach aided by code assisting tools(Codex/Windsurf/Claude).
Team & Key Projects
• Team: E-Commerce MLOps
• Purpose: Provide a Machine Learning Engineers and Data Scientists a fully featured platform for Research and Development.
• Reason: Help data scientists to migrate workloads faster
• Motivation: Complete the desired goals before the end of the year
Typical Day in the Role:
• Get familiarized with the platform and ways of working.
• Migrate existing pipelines into the platform following best engineering practices
• Fully integrated into the team
• Self-started, minimal hand-holding
Candidate Requirements:
Experience: 5+ years of software engineering, DevOps, or MLOps experience.
• Core Languages & Libraries: Strong proficiency in Python, SQL, and Pandas. Experience with
Bash scripts and Golang are a plus.
• Containerization & Orchestration: Deep, hands-on experience with Docker and self-hosted
Kubernetes. Should be able to run pipelines on local machine with a small amount of data.
• Engineering Practices: Demonstrated experience with Test-Driven Development (TDD) and
formal requirement gathering.
• CI/CD & Deployment: Proven experience with continuous integration/continuous
deployment (CI/CD) pipelines, and modern version control (Git).
• Workflow: High proficiency operating within command-line (CLI) environments and utilizing
AI code-assisting tools.
Top 3 Skills:
Experience with Production Ready Software development lifecycle
Good engineering Practices (Unit Tests, Source control, Collaboration)
Should be able to run a prototype end to end locally, in a containerized environment
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