Customer Reliability Engineer

fluidstack; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Fluidstack is seeking a Data Center Operations professional to own reliability for customer workloads and coordinate across teams. You’ll debug across the full stack and manage incident communications with depth and clarity, driving fixes from production through engineering.

This role suits those with experience supporting HPC/cloud/AI labs and a track record of preventing repeat issues. You will push internal teams to address root causes and maintain SLAs while operating at scale beyond a

Qualifications

• 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 have written incident updates customers trusted more after reading.
• You push internal teams to fix causes, not symptoms, and follow up until they do.

Responsibilities

• 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.

Skills

Large-scale compute experience

Distributed systems debugging

Incident communication

Root-cause analysis

Tools

Slurm

Kubernetes

NCCL

InfiniBand / RoCE

Job description

The Data Center Operations Team

Examples of key problems the team is working on:

• Operate at the scale of a nation, not a building. The fleet you run will draw more power than some countries, on the way to 100 GW.
• Fly the plane while it’s being built. Sites come online in pieces, and you keep the live ones running flawlessly while construction continues around them.
• Write the playbook, don’t inherit it. No prior operations org has run at this speed and scale, so the standards you set become the standard.

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

• 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 have 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.

Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.