Staff Network Engineer at Lambda

San Francisco, California, United States

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$284,000 – $473,000Compensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Cloud Computing, TechnologyIndustries

Requirements

15+ years of experience in designing and operating production datacenter networks
Have led the implementation of large production-scale networking projects
Expert in CLOS/Spine and Leaf fabrics, EVPN/VXLAN, ECMP, BGP, and fast convergence techniques
Have experience with multi-data center networks, backbone and hybrid cloud networks
Production experience with at least two switches/routers vendors (e.g., Arista, Juniper, Cisco, NVIDIA/Mellanox, Cumulus/SONiC)
Experience with Next-Generation Firewalls (NGFW) (e.g. Fortigate, Juniper)
Experience with LoadBalancers like F5, NetScaler
Are comfortable on the Linux command line, and have an understanding of the Linux networking stack
Strong automation skills (Python, Ansible) and network APIs
Nice To Have
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
Experience with Observability tools like Datadog, Splunk, Grafana, Prometheus
Experience automating network configuration within public clouds, with tools like Terraform
Have led implementation of production-scale SDNs in a cloud context (e.g. helped implement the infrastructure that powers an AWS VPC-like feature)
Deep understanding of the Linux networking stack and its interaction with network virtualization
Experience with SDN ecosystem (e.g. OVS, Neutron, DPDK, Cisco ACI or Nexus Fabric Controller, Arista CVP)

Responsibilities

Help scale Lambda’s high performance cloud network
Contribute to the reproducible automation of network configuration
Contribute to the design and development of software defined networks
Help manage Spine and Leaf networks
Ensure high availability of our network through monitoring, failover, and redundancy
Ensure VMs/clients have predictable networking performance through the use of QoS and other applicable technologies
Help with deploying and maintaining network monitoring and management tools

Skills

Spine and Leaf

EVPN

VXLAN

ECMP

BGP

Arista

Juniper

Cisco

NVIDIA/Mellanox

Cumulus/SONiC

Fortigate

NetScaler

Python

Ansible

Linux

Lambda

Cloud-based GPU services for AI training

About Lambda

Lambda Labs provides cloud-based services for artificial intelligence (AI) training and inference, focusing on large language models and generative AI. Their main product, the AI Developer Cloud, utilizes NVIDIA's GH200 Grace Hopper™ Superchip to deliver efficient and cost-effective GPU resources. Customers can access on-demand and reserved cloud GPUs, which are essential for processing large datasets quickly, with pricing starting at $1.99 per hour for NVIDIA H100 instances. Lambda Labs serves AI developers and companies needing extensive GPU deployments, offering competitive pricing and infrastructure ownership options through their Lambda Echelon service. Additionally, they provide Lambda Stack, a software solution that simplifies the installation and management of AI-related tools for over 50,000 machine learning teams. The goal of Lambda Labs is to support AI development by providing accessible and efficient cloud GPU services.

San Jose, CaliforniaHeadquarters

2012Year Founded

$372.6MTotal Funding

DEBTCompany Stage

AI & Machine LearningIndustries

201-500Employees

Risks

Nebius' holistic cloud platform challenges Lambda's market share in AI infrastructure.

AWS's 896-core instance may draw customers seeking high-performance cloud solutions.

Existential crisis in Hermes 3 model raises concerns about Lambda's AI model reliability.

Differentiation

Lambda offers cost-effective Inference API for AI model deployment without infrastructure maintenance.

Nvidia HGX H100 and Quantum-2 InfiniBand Clusters enhance Lambda's AI model training capabilities.

Lambda's Hermes 3 collaboration showcases advanced AI model development expertise.

Upsides

Inference API launch attracts enterprises seeking low-cost AI deployment solutions.

Nvidia HGX H100 clusters provide competitive edge in high-performance AI computing.

Strong AI cloud service growth indicates rising demand for Lambda's GPU offerings.

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