Member of Technical Staff - GPU Infrastructure Engineer

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via Ashby

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About this role

ABOUT LIQUID AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there. THE OPPORTUNITY Our Cluster Infrastructure team owns the compute environments that power foundation model training and research at Liquid AI. We are looking for a hands-on software engineer to keep our GPU clusters reliable, improve resource efficiency, and build the tooling that allows researchers to focus on model development rather than infrastructure.…

Read the full description on Liquid Ai's site →

What we'd score you on

reqspace match rubric

Five dimensions, recruiter-grade. Upload your resume and we'll generate a written explanation of where you fit and where the gaps are.

Skills match

For this role: go, less, kubernetes, hadoop, ray…

Level fit

This role is mid-level. We check your trajectory against it.

Domain experience

Your work in the role's domain matters more than your years total. We weight recent and direct experience.

Recency

A skill you used last quarter weighs more than one from five years ago. We grade on recency, not lifetime.

Location fit

This role is remote-eligible — we factor in your stated location and time-zone overlap.

Score yourself on this role.

Free · no card · written explanation included

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Skills in this role

Pulled from the job description. These are the keywords we'll weight when scoring your fit.

golesskuberneteshadooprayteams

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