LambdaSenior HPC Engineer - Fleet Engineering
Lambda is hiring a Senior HPC Engineer - Fleet Engineering for a remote role open to applicants in United States. It pays $227k-$356k a year and Level rates it ; you can apply on Lambda.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- The posting lists this role as remote.
- Tools and skills the posting cites include PyTorch, TensorFlow and Ansible.
- Level classifies it as a senior role.
- Level lists 96 other open roles at Lambda.
AI in this role
Build, automate, and operate large-scale GPU-first HPC clusters and AI cloud infrastructure for demanding machine learning workloads.
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.
What You’ll Do
Build and operate monitoring and alerting for cluster health — fabric, GPU, power/thermal, and job-level signals — to detect and respond to issues proactively
Remotely deploy and configure large-scale HPC clusters for AI workloads using automation wherever possible
Automate cluster lifecycle: operating systems, firmware, drivers, and networking, managed as code (Ansible, Terraform) rather than by hand
Create runbooks and automated remediations for common cluster failure modes, designed so Support and HPC Support can run them safely
Troubleshoot and resolve cluster issues across InfiniBand/RoCE, NCCL, GPU-direct, fabric, switching, and power — working closely with on-site deployment teams
Participate in on-call rotations and lead incident response for cluster-level problems
Contribute to and maintain Standard Operating Procedures, and feed clear requirements back to other engineering teams on simplification, stability, and operational efficiency
You
7+ years of experience in Site Reliability Engineering, HPC Engineering, DevOps, or a similar role
Have a strong understanding of modern AI infrastructure, from GPU architectures to hardware performance optimization
Strong understanding of Linux-based systems in a distributed environment
Are experienced configuring and troubleshooting InfiniBand (IB), RoCE, CLOS fabrics, 100GbE, Ethernet/switching, GPU-direct, and NCCL environments
Solid understanding of Python and Go, with experience working with SWE teams to improve internal tooling.
Experience with monitoring and alerting tools (e.g., Prometheus, Grafana, Clickhouse)
Proficiency in automation and configuration management tools (e.g., Ansible, Terraform)
Have excellent problem-solving and troubleshooting skills and an innate attention to detail
Passion for continuous improvement and innovation
Nice to Have
Experience with machine learning / deep learning frameworks (PyTorch, TensorFlow) and benchmarking tools (DeepSpeed, MLPerf)
Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes)
Experience building and/or operating HPC resources.
Depth in the NVIDIA hardware and firmware ecosystem
Experience with data center power and thermal design
Background in chaos engineering or similar reliability testing methodologies
Understanding of compliance frameworks (SOC 2, ISO 27001, etc.)
Salary Range Information
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.
How we rate this
Senior HPC Engineer - Fleet Engineering at Lambda rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● 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 hpc engineering was part of your work. What did you do?
- Tell me about a project where site reliability engineering was part of your work. What did you do?
- Tell me about a project where gpu infrastructure was part of your work. What did you do?
- Tell me about a project where cluster management 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?
Adapt your resume
- List these exact terms on your resume: Hpc Engineering, Site Reliability Engineering, GPU Infrastructure, Cluster Management, and Automation. 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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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