Hyperbolic
Forward Deployed Infrastructure Engineer
NEWRemoteFull-timeGlobal
š Remote
RemoteRemote work position availableActivePosted within the last 30 days
Job Description
[AI-summarized by JobStash]
You will serve as the technical point of contact during customer trials, running standardized and custom benchmarks to validate performance. You will design, run, and analyze performance tests across customer workloads, diagnose GPU and NCCL issues, optimize container and cluster configurations, and produce clear reports and handoffs. You will maintain benchmarking scripts, containers, and environments and iterate on configurations to close performance gaps.
Requirements
- āExperience running infrastructure performance tests or ML model benchmarks (training or inference)
- āStrong knowledge of GPU cloud infrastructure and workload bottlenecks
- āClear and fast written communication
- āAbility to manage multiple trials and projects concurrently
- āFamiliarity with AWS Lambda CoreWeave Runpod and similar GPU cloud providers
- āPrior customer-facing experience in startup or devtools settings (preferred)
- āBackground as an ML engineer solutions architect or technical account manager (preferred)
Responsibilities
- āServe as the technical point of contact during customer trials
- āDesign and run performance and benchmark tests across customer workloads
- āDiagnose performance issues and recommend fixes
- āPackage results into clear reports and handoffs
- āMaintain benchmarking scripts containers and environments
- āIdentify performance gaps and optimize cluster configurations
Tech Stack
model benchmarkingcontainer configurationAWScontainerbenchmarkingMLGPUInferencecloud infrastructuretraining