HPC Support Engineer

Lambda; United States; On-site; USD 122,000 - 162,000; Full time

Benefits offered by this job

Health coverage

Dental

Vision

Wellness stipend

Commuter stipend

401k matched

Flexible PTO

Job summary

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure providing services to researchers, enterprises, and hyperscalers. This role is based in the United States and participates in an on-call rotation to handle the most challenging infrastructure and platform issues.

You will act as a senior escalation point, differentiate among hardware, driver, and kernel problems, and drive permanent fixes by collaborating with engineering and documenting solutions.

Qualifications

• 3+ years in HPC administration, support, or engineering.
• Strong Linux system administration experience.
• Experience with Kubernetes and/or Slurm for cluster orchestration.

Responsibilities

• Serve as senior escalation point for infra issues down to hardware/kernel level.
• Differentiate hardware, driver, kernel, and workload misconfig to resolve issues quickly.
• Identify gaps in processes, tooling, and docs and fix them.
• Build scripts or small tools using AI-assisted techniques to close gaps.
• Perform root-cause analysis across distributed systems and GPU clusters.
• Document solutions and contribute to support procedures.

Skills

HPC administration

Linux admin

Kubernetes

Slurm

CI/CD

AI tooling

Monitoring tools

Kernel debugging

CUDA/NVLink

Networking IB/RoCE

Distributed AI/ML

Cloud networking

Tools

Docker

Terraform

Ansible

Prometheus

Grafana

Datadog

NVIDIA GPU tools

Job description

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.

If you'd like to build the world's best AI cloud, join us.

This position is expected to participate in an on‑call rotation.

What You’ll Do

• Serve as a senior technical escalation point, troubleshooting the hardest infrastructure and platform issues down to the hardware, driver, or kernel level when needed
• Quickly and accurately distinguish between hardware failures, driver issues, kernel‑level problems, and customer workload misconfiguration, so issues get resolved correctly the first time
• Proactively identify process, tooling, and documentation gaps, and go fix them, not just wait for them to be assigned
• Use AI tools effectively to build scripts, automations, or small internal tools that close real operational gaps (no professional development background required)
• Perform root‑cause analysis across distributed systems, clusters, and GPU infrastructure
• Craft clear documentation of solutions and contribute to evolving support procedures
• Collaborate closely with engineering teams to turn recurring customer pain points into permanent fixes
• Take escalations from peers while training and mentoring them in the process
• Participate in a rotating on‑call schedule, owning major incidents and major customer issues
• Be ready to roll up your sleeves and pitch in wherever needed, especially during fast, high‑volume deployments

You

• 3+ years of hands‑on HPC experience in an administration, support, or engineering role.
• Very strong understanding and experience supporting Linux in a system administration role.
• Proven experience in HPC environments, showcasing your expertise in Linux cluster administration, with strong preference for Kubernetes and/or Slurm for cluster orchestration.
• Strong coding ability and CI/CD experience, with a track record of using AI‑assisted tools to move fast.
• Proficiency with monitoring/logging tools (Prometheus, Grafana, Datadog).
• Strong skills in log analysis, debugging kernel‑level issues, and performance profiling.
• Experience with CUDA, NCCL, NVLink, GPUDirect RDMA.
• Experience with high throughput networking technologies(IB/RoCE).
• Knowledge of distributed AI/ML or HPC workloads.
• Knowledge of TCP/IP, VPN, and firewalls in cloud environments.
• Ability to work independently and mentor junior support engineers.

Nice to Have

• Experience with virtualization and container (Docker, Kubernetes) technologies.
• Experience with neoclouds/GPU cloud providers.
• Flexible availability for potential shifts outside of normal working hours/weekends.
• Experience with high performance storage systems.
• Familiarity with infrastructure‑as‑code tools (Terraform, Ansible, etc.)
• Experience with Nvidia GPUs and Infiniband.

Salary Range Information

This is a salaried exempt role. The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

About Lambda

• Founded in 2012, with 500+ employees, and growing fast
• Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In‑Q‑Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
• We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
• Our values are publicly available: https://lambda.ai/careers
• We offer generous cash & equity compensation
• Health, dental, and vision coverage for you and your dependents
• Wellness and commuter stipends for select roles
• 401k Plan with 2% company match (USA employees)
• Flexible paid time off plan that we all actually use

Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

Compensation Range: $122K - $162K