Senior Site Reliability Engineer - Networking at Lambda

San Francisco, California, United States

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$250,000 – $417,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Cloud Computing, AIIndustries

Requirements

5+ years of experience as SWE, SRE or Network Reliability Engineering
Experience being part of the implementation of production-scale networking projects
Experience being on-call and incident response management
Experience building and maintaining Software Defined Networks (SDN), experience with OpenStack, Neutron, OVN
Comfortable on the Linux command line, and understanding of the Linux networking stack
Experience with multi-data center networks and hybrid cloud networks
Python programming experience and configuration management tools like Ansible
Experience with CI/CD tools for deployment and GIT; operated network environment with GitOps practices
Experience with application lifecycle and deployments on Kubernetes

Responsibilities

Help scale Lambda’s high performance multi-tenant cloud network
Contribute to the reproducible automation of network configuration and deployments
Contribute to the implementation and operations of Software Defined Networks
Help to deploy and manage Spine and Leaf networks
Ensure high availability of our network through observability, failover, and redundancy
Ensure clients have predictable networking performance through the use of network engineering and other applicable technologies
Help with deploying and maintaining network monitoring and management tools
Participate in on-call

Skills

SRE

Networking

Software Defined Networks

SDN

OpenStack

Neutron

OVN

Linux

Ansible

Python

CI/CD

Spine and Leaf

Multi-data center networks

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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