Manager, HPC Design at Lambda

San Francisco, California, United States

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$330,000 – $550,000Compensation

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

Full TimeJob Type

UnknownVisa

AI, High Performance Computing, Cloud ComputingIndustries

Requirements

5+ years of experience designing HPC or cloud infrastructure at scale
2+ years in a technical leadership or management role
Understand the practical application of compute, storage, and network architectures in real-world, large-scale deployments
Can take an established architectural direction and lead your team in producing high-quality designs that deliver reliably, on-time, and within scope
Adept at managing tradeoffs and risk in infrastructure delivery—balancing technical ambition with operational realism
Experience mentoring senior-level technical contributors and building cohesive, execution-focused teams

Responsibilities

Lead a team of system designers responsible for translating architecture into detailed, executable infrastructure designs across compute, storage, and networking
Build and mature repeatable processes that turn Lambda’s reference architectures into site and customer-specific deployment plans
Own the delivery of infrastructure design packages, ensuring solutions meet functional requirements, budget targets, and delivery timelines
Partner closely with architecture, product, engineering, and customer teams to ensure alignment between design execution and platform roadmap
Guide the creation and review of design specifications, integration plans, and validation processes for new deployments
Mentor and grow a high-performing team of infrastructure designers, focused on disciplined execution and iterative delivery

Skills

HPC

Infrastructure Design

Compute Architecture

Storage Architecture

Networking

Cloud Infrastructure

System Deployment

Deployment Plans

Reference Architectures

Validation Processes

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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