Staff Machine Learning Systems Engineer

Staff Machine Learning Systems Engineer at Jobgether scores 93 out of 100 on AI centrality, which makes it a Level 4 role on this board.

Remote (US)leadFull-time

AI in this role

ml-ops

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Machine Learning Systems Engineer based in the United States.

This senior technical role focuses on building and scaling the infrastructure that powers large-scale machine learning systems.
You will design end-to-end MLOps patterns that accelerate model development, experimentation, deployment, and iteration.
The position combines platform engineering, distributed ML, data processing, performance optimization, and cloud infrastructure.
You will help develop scalable graph machine learning platforms capable of handling billions of nodes and tens of billions of edges.
Working closely with machine learning engineers, you will improve training performance, resource efficiency, reliability, and GPU utilization.
The role offers significant technical ownership in a distributed, cloud-based environment where scalability and ease of use are critical.
You will also serve as a strong advocate for platform users while shaping engineering practices and infrastructure that enable teams to move faster.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Ml Ops

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Ml Ops. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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