Staff HPC Hardware Engineer at Lambda

San Jose, California, United States

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$349,000 – $581,000Compensation

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

Full TimeJob Type

UnknownVisa

High Performance Computing, AI, Cloud Infrastructure, Data CentersIndustries

Requirements

7+ years of experience in hardware integration or systems engineering for HPC, data center, or cloud infrastructure environments
Deep knowledge of server hardware platforms (x86 and ARM), PCIe accelerators, storage devices, and network fabrics
Experienced with vendor-led product development cycles and can drive hardware evaluation, risk mitigation, and feedback into roadmap decisions
Can interpret platform-level architecture requirements and select or adapt OEM solutions to fit
Comfortable working hands-on in labs with rack-scale deployments, BIOS/firmware tuning, and performance validation
Collaborate well across architecture, design, engineering, and vendor teams to deliver complete, production-ready hardware solutions

Responsibilities

Serve as the technical lead for integrating OEM and white-label compute, storage, and network hardware into Lambda’s HPC platform reference architectures
Drive the end-to-end process of new product introduction (NPI) for hardware systems, including evaluation, validation, documentation, and production readiness
Partner with architects to translate platform blueprints into concrete hardware selections and system configurations
Work cross-functionally with design, engineering, operations, and vendor engineering teams to ensure compatibility, performance, and scalability of new systems
Identify and resolve hardware issues across thermal, power, firmware, and mechanical domains during evaluation and bring-up cycles
Provide technical guidance during vendor engagements and benchmarking of next-generation platforms

Skills

HPC

Hardware Integration

Systems Engineering

x86

ARM

PCIe

Accelerators

Storage Devices

Network Fabrics

Thermal Management

Power Systems

Firmware

Mechanical

NPI

Vendor Management

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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