IT Systems Engineer, Infrastructure & Platform Reliability at Lambda

San Francisco, California, United States

Lambda Logo
$206,000 – $310,000Compensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Technology, AI, Cloud ComputingIndustries

Requirements

  • Keen interest in system design, architecting for performance, scalability, and experience with multiple cloud infrastructure platforms (AWS, GCP, Azure, etc.)
  • Think carefully about systems: edge cases, failure modes, behaviors, and specific implementations
  • Know and prefer configuration management systems and toolchains (Chef, Ansible, Terraform, GitHub Actions, etc.)
  • Solid programming skills: Python, Go, etc
  • Urge to collaborate and communicate asynchronously, combined with a desire to record and document issues and solutions
  • Enthusiastic, go-for-it attitude; fix things when broken
  • Urge for delivering quickly and effectively, and iterating fast

Responsibilities

  • Design, write, and deliver software and services to improve the availability, scalability, reliability, and efficiency of Lambda’s internal IT systems and platforms
  • Solve problems relating to mission critical services and build automation to prevent problem recurrence with the goal of automating response to all non-exceptional events
  • Work with Lambda Engineering and internal teams to influence and create new designs, architectures, standards, and methods for large-scale distributed systems
  • Engage in service capacity planning and demand forecasting, software performance analysis, and system tuning
  • Be an excellent communicator, producing documentation and related artifacts for the systems you are responsible for

Skills

AWS
GCP
Azure
Configuration Management
System Design
Scalability
Reliability
Automation
Capacity Planning
Performance Analysis
Distributed Systems

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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