Customer Reliability Engineer

Fluidstack

$120K — $150K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Experience supporting large-scale compute customers like HPC, cloud, or AI labs.
  • Methodical debugging of distributed systems across multiple layers.
  • Proficient in drafting trustworthy incident updates for customers.
  • Ability to advocate for root cause fixes with internal teams.
  • Bonus: Familiarity with GPU training workloads and technologies such as InfiniBand, RoCE, Slurm, or Kubernetes.

Responsibilities

  • Own reliability of designated customer workloads including clusters, SLAs, and escalations.
  • Debug issues across the entire stack, from hardware to scheduler, during training run deficiencies.
  • Manage customer-facing incident communications with depth and honesty.
  • Transform ongoing customer challenges into engineering solutions with production teams.

Benefits

  • Commitment to pay equity and transparency.
Full Job Description
Role Scope
  • Own reliability for named customer workloads: their clusters, their SLAs, their escalations.
  • Debug across the full stack, hardware to fabric to scheduler, when a training run degrades.
  • Run customer-facing incident communication with technical depth and no spin.
  • Turn recurring customer pain into engineering fixes with the production teams.

What We're Looking For

The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would.
  • You've supported large-scale compute customers (HPC, cloud, or AI labs) at a technical level.
  • You debug distributed systems methodically across layers you don't own.
  • You've written incident updates customers trusted more after reading.
  • You push internal teams to fix causes, not symptoms, and follow up until they do.
  • Bonus: GPU training workloads. InfiniBand or RoCE. Slurm or Kubernetes. NCCL debugging.


We are committed to pay equity and transparency.

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