Forward Deployed Infrastructure Engineer

Hyperbolic Labs

Completely RemoteFull TimeInformation Technology
Posted Today

Job description

About the Company

Hyperbolic Labs is on a mission to democratize AI by breaking down the barriers to computing power with our Open-Access AI Cloud. By aggregating computing resources across the globe, we offer an innovative GPU marketplace and AI inference service that promise affordability and accessibility for all.

Responsibilities

  • Act as the technical point-of-contact during customer trials, running standardized and custom benchmarks
  • Design, run, and analyze performance tests across customer workloads, including comparisons against AWS and Lambda
  • Diagnose performance issues related to GPU utilization, NCCL setup, and container configurations
  • Package technical results into clear, credible reports and documentation
  • Maintain benchmarking infrastructure, including scripts, containers, and environments
  • Identify performance gaps and work with supply and engineering teams to optimize cluster configurations

Requirements

  • Experience running infrastructure performance tests or ML model benchmarks (training or inference)
  • Strong knowledge of GPU cloud infrastructure and workload bottlenecks
  • Clear and fast written communication skills for reports and documentation
  • Ability to manage multiple trials and projects simultaneously
  • Familiarity with the GPU cloud landscape (AWS, Lambda, CoreWeave, Runpod, etc.)

Preferred Qualifications

  • Prior customer-facing experience in a startup or devtools setting
  • Background as an ML engineer, solutions architect, or technical account manager

Skills & tools

GPUMachine LearningInfrastructure

What the team is looking for

Use this list as a quick fit check before you apply.

  1. 01Experience running infra performance tests or ML model benchmarks
  2. 02Strong knowledge of GPU cloud infra
  3. 03Clear and fast written communication
  4. 04Ability to juggle multiple trials/projects
  5. 05Familiarity with AWS, Lambda, CoreWeave, or Runpod
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