Senior Site Reliability Engineer

Lambda•San Francisco, CA

1d•$240,000 - $356,000•Hybrid

About The Position

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. Note: This position requires presence in our San Francisco or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

Requirements

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 Haves

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.)

Responsibilities

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