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GPU Reliability Engineer at Thinking Machines Lab - ApplyBlast

GPU Reliability Engineer

Thinking Machines Lab

3 months ago

Remote

Full Time

Senior

0 applicants

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About this role

The role focuses on ensuring the reliability of a large GPU supercomputing fleet by diagnosing hardware issues, managing firmware lifecycles, and collaborating directly with vendors to implement fixes. The engineer will automate monitoring, analyze error rates, and produce clear postmortems and vendor cases to improve system stability.

Responsibilities

Investigate and remediate issues across large GPU clusters
Drive firmware lifecycle including qualification, rollout, and regression analysis
Engage hardware vendors to resolve failures and manage RMA flows

Skills

Qualifications

Bachelor's degree in Computer Science, Engineering, or related field

About Thinking Machines Lab

thinkingmachines.ai

Headquarters

San Francisco, California, United States

Company Size

1-10 employees

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Thinking Machines Lab is an artificial intelligence research and product company focused on making advanced AI systems more widely understood, customizable, and generally capable. They aim to close gaps between rapidly advancing capabilities and the scientific/public understanding of how these systems are trained and used. Through research, public-facing writing (the Connectionism blog), and products such as their recently introduced Tinker, they build tools and knowledge to help people and organizations tailor AI to their needs and values.