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Lambda

Cloud-based GPU services for AI training

Senior Site Reliability Engineer - SDN

Site Reliability EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Have 5 or more years of experience in Site Reliability Engineering, Production Engineering, or a similar role.
  • Have experience operating and supporting large-scale distributed systems in production.
  • Have experience with Kubernetes application lifecycle management, upgrades, troubleshooting, and production operations.
  • Have experience participating in on-call rotations and incident response.
  • Have strong troubleshooting skills across Linux systems, Kubernetes, distributed systems, and networking.
  • Have experience with observability platforms, monitoring, alerting, and metrics.
  • Be comfortable working on the Linux command line and have a solid understanding of the Linux networking stack.
  • Have experience with multi-datacenter and hybrid cloud environments.
  • Have experience automating infrastructure and operational workflows using Python, Ansible, or similar tools.
  • Have experience designing and operating CI/CD and GitOps deployment workflows.

Responsibilities

  • Operate and scale the multi-tenant cloud networking platform and SDN infrastructure.
  • Operate and improve Kubernetes-based control plane services and dataplane software running on SmartNICs.
  • Develop tooling and automation to reduce operational toil and improve reliability.
  • Collaborate with software, platform, and networking teams to improve service reliability and deployment workflows.
  • Deploy and maintain network monitoring, observability, and management tools.
  • Improve deployment safety through CI/CD pipelines, GitOps workflows, testing, and progressive rollouts.
  • Drive operational excellence through observability, incident management, capacity planning, postmortems, and participation in the on-call rotation.

Desired Qualifications

  • Experience building and operating Software Defined Networks (SDN), including OpenStack Neutron, OVN, and OVS.
  • Experience operating production-scale SDNs in a cloud environment, such as infrastructure powering AWS VPC-like networking services.
  • Software development experience in Go and/or Python; C is a plus.
  • Experience automating infrastructure and network configuration using Kubernetes, Helm, Terraform, and Ansible.
  • Deep understanding of the Linux networking stack and its interaction with network virtualization technologies, SR-IOV, and DPDK.
  • Understanding of the SDN ecosystem and modern cloud networking architectures.
  • Experience diagnosing complex production issues across infrastructure, networking, and application layers.

About the Company

Lambda

Cloud-based GPU services for AI training

Lambda Labs provides cloud-based GPU services for AI training and inference via its AI Developer Cloud, powered by NVIDIA GH200 Grace Hopper hardware to efficiently train large language models and generative AI. Customers access on-demand or reserved GPUs and are billed by the hour (for example, NVIDIA H100 at about $1.99/hour); it also offers Lambda Echelon, where clients own infrastructure but pay a monthly hosting and support fee, and Lambda Stack, a software suite that helps ML teams install and upgrade tools like PyTorch, TensorFlow, CUDA, cuDNN, and NVIDIA drivers. The company differentiates itself through competitive pricing, available high-end hardware, and an integrated ML software stack that streamlines workflows. Its goal is to enable scalable, affordable AI development and deployment by providing flexible GPU access, reliable hosting, and easy software deployment for teams working with large models.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$9.1B
Headquarters
San Jose, CA
Founded
2012

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