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HPC Support Engineer

Lambda · Remote

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Last seen by MeritLog September 8, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from Lambda's Ashby job board and last checked it on September 8, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model
Remote
Salary
$122K - $162K
Location
Remote, USA

Hiring context

How this role compares at Lambda

Lambda has 86 live roles in MeritLog’s catalog across 10 job families, and 30 of them are in engineering. 83 of those listings publish a pay range, a disclosure rate of 97%.

This role's posted range of $122K - $162K sits above 10% of the 79 other Lambda roles quoted over the same currency and period.

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd 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
  • 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.

What they're asking for

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

Parsed by MeritLog from the employer’s own posting. The full description follows below.

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.

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