We're looking for an ML Performance Engineer to join our MLOps team. You will validate new clusters by running large-scale training and inference workloads, help improve our managed Kubernetes and Slurm platforms through hands-on use, and produce performance benchmarks for customers and the broader market.

Validate new cluster deployments by running large-scale training and inference workloads before customer handoff

Identify, reproduce, and diagnose performance and reliability issues, working with infrastructure and platform teams to resolve them

Use our managed Kubernetes and Slurm platforms the way our customers do, and provide feedback that improves them

Run model benchmarks across training and inference, both for internal and external use

Build tooling and repeatable workflows for validation and benchmarking

Stay current with distributed training and inference frameworks and their performance on AMD Instinct GPUs

Work with larger MLOps team to help support customer clusters and workloads

ML Performance Engineer

Responsibilities

Qualification

Required

Benefits

Company

Tensorwave

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