Supercompute Operations Engineering
xAI is hiring a Supercompute Operations Engineering . Level rates it ; you can apply on xAI.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Dcgm, Prometheus and Grafana.
- Level classifies it as a mid-level role.
- Level lists 296 other open roles at xAI.
- The role was posted in the last few days.
AI in this role
Manage 24/7 GPU cluster uptime, datacenter operations, and infrastructure automation for massive AI supercomputers.
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.
SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.
ABOUT THE ROLE:
This team owns 100% GPU uptime, end to end, 24/7, across both compute and facility. It owns incident response and the engineering behind it, holds central control authority from the customer back to the facility, runs day-to-day sustainment of live datahalls, and leads deployment engineering for new datahall bring-up. The team will also build the automation for continuous response improvement. The team is expected to have system level knowledge about the whole datacenter site, end to end. The team engineers solutions to enable GPU uptime, working directly with technicians in the datahalls and field to execute the team’s engineering planning.
RESPONSIBILITIES:
- Own monitoring architecture, alerting, signal quality, and automation of monitoring across GPU and host telemetry (DCGM, Prometheus/Grafana) and facility telemetry (BMS, EPMS, DCIM, SCADA, CDU / direct liquid cooling).
- Own compute hardware change incorporation - physical, firmware, software.
- Be part of 24/7 iincident response, mitigation, and control authority - end to end - from customer impact back to the facility.
- Own day-to-day site sustainment operations, including resolving issues impacting rack-level compute and facility infrastructure.
- Disposition daily issues across both Site Operations (rack compute) and Facility Operations (power and cooling).
- Lead acceptance and deployment testing campaigns to bring new data halls fully online.
- Develop production automation for new datahall bring-up, automation behind alerting and automated incident response.
- Develop and maintain standard operating procedures and planning for facility and site technicians. Includes change / upgrade incorporation planning on both rack level and facility.
- Own and document the live, changing state of datahall operation as new halls come online.
- Enable Site Operations and Facility Operations technicians to do their day to day jobs more efficiently and safely to increase GPU uptime.
- Create predictive and responsive automation to alerts and incidents to enable your response to be faster and more impactful.
- Lead cross-functional reliability projects spanning compute, network (InfiniBand/RoCE), storage, and facility signal boundaries, including grey failures that cross those boundaries (e.g., NVLink flapping, thermal throttling, power sequencing).
- Truly root cause systemic and design failure classes across hardware and integrated facility and operations systems: turn fleet data (MTBF/AFR, repeat-RMA trends) into proactive alerting, standard responses, vendor RCA inputs, and supplier corrective actions.
BASIC QUALIFICATIONS:
- Bachelor's degree in Mechanical, Electrical, or Computer Engineering or a related scientific discipline and 2+ years of experience in data center, critical facilities, power plant, or large-scale compute operations; or 6+ years of equivalent experience in those environments.
PREFERRED SKILLS AND EXPERIENCE:
- Hands-on experience with at least one of: Prometheus/Grafana, NVIDIA DCGM, or industrial telemetry and controls (SCADA, BMS/BAS, EPMS, DCIM, PLCs, Modbus/BACnet).
- Experience in datacenter site reliability, systems engineering, plant operations, or large-scale production operations.
- Experience running acceptance test campaigns for integrated products.
- Experience in AI/ML infrastructure or supercomputing environments: GB200/NVL72 or H100/H200-class GPU fleets, NCCL, InfiniBand/RoCE, Slurm or Kubernetes.
- Fleet firmware and BMC management (Redfish, IPMI), including firmware release validation and staged rollouts.
- Familiarity with data center hardware and plant signals (servers, GPUs, networking, power, cooling) in addition to software telemetry.
- Proven large-scale incident command experience and calm technical leadership on a bridge, whether from an SRE/NOC bridge or a plant control room.
- Experience writing and operating playbooks, runbooks, or standard operating procedures, methods of procedure, emergency operations procedures.
- Proficiency in scripting (Python, Bash) for automation and analysis, plus general experience in at least one systems language (C, C++, Java, Go, Rust, or similar).
- Ability to work collaboratively with cross-functional, cross-country, multi-disciplinary teams.
SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
How we rate this
Supercompute Operations Engineering at xAI rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where gpu infrastructure was part of your work. What did you do?
- Tell me about a project where datacenter operations was part of your work. What did you do?
- Tell me about a project where incident response was part of your work. What did you do?
- Tell me about a project where automation was part of your work. What did you do?
- Walk me through how you've used Dcgm in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: GPU Infrastructure, Datacenter Operations, Incident Response, Automation, and Dcgm. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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