Build and operate infrastructure for large-scale training and evaluation, improving reliability
Develop shared inference and grading platforms with automated capacity management, health
Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads
Diagnose bottlenecks across training, inference, and orchestration, and work across teams to
Build self-service tools, automated validation, and observability that help researchers launch

🎯 Requirements

Strong software engineering fundamentals and experience building or operating large-scale
Experience in ML infrastructure, inference systems, GPU performance, or infrastructure tooling.
Highly self-motivated and comfortable taking ownership of open-ended problems.
Enjoy debugging across system boundaries and using measurements to guide improvements in

🎁 Benefits

Offers Equity

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