Senior Network Engineer
Lambda
Senior Network Engineer
Lambda
Cloud-based GPU services for AI training
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, San Jose, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.
What You’ll Do
Help to build and scale Lambda's high performance cloud network
Work on deploying and configuring networking Hardware for new and existing clusters
Ensure high availability of our network through monitoring, failover, and redundancy
Contribute to automation of network configuration management and operation
Work with internal and external customers to resolve network related issues
Help with deploying and maintaining network monitoring and management tools
Will be part of day2 operations and on-call rotation for Network Engineering team
You
Have 10+ years of experience in IT and networking space
Have 6+ years of experience in designing and operating production Data Center type of networks
Have led the implementation of large production-scale networking projects
Experience managing Next-Generation Firewalls (e.g. Fortigate)
Have experience with cloud providers networking (such as AWS, GCP, OCI)
Expert in CLOS/Spine and Leaf fabrics,EVPN/VXLAN, ECMP, BGP, and fast convergence techniques.
Are comfortable on the Linux command line, and have an understanding of the Linux networking stack and internals
Strong automation skills (Python, Ansible) and network APIs and worked with git or similar source control systems
Production experience with multiple network gear vendors (Arista, Juniper, Cisco, Cumulus/SONiC, Opengear)
Experience with Networking Monitoring stack (Datadog, Clickhouse, Grafana, Prometheus, gNMI, OTel)
Nice to Have
Have knowledge or experience maintaining Software Defined Networks (SDN)
Experience automating network configuration within public clouds, with tools like Terraform/Ansible/Salt
Hands-on with HPC/AI networking: RoCEv2 and/or InfiniBand (Congestion Control, VLs, partitions), GPUDirect RDMA concepts.
Experience with DWDM technologies and SD-WAN
Understanding of data center power/space/cooling trade-offs and their impact on topology choices
Have experience with virtualization technology, like ESXi, KVM, and VMs management
Experience with LoadBalancers like F5, NetScaler
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.
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.
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