QA Engineer at Lambda

San Jose, California, United States

Apply Now

$135,000 – $203,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Cloud Computing, HardwareIndustries

Requirements

Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or equivalent practical experience
5+ years of experience in MFG/HW test experience across electronics, optical, aerospace or related space
Familiar with common lab equipment such as: Power Supplies, Oscilloscopes, Optical Test Equipment, Signal Generators, DMMs, Logic Analyzers, etc
Demonstrated proficiency in Python
Understanding of networking fundamentals in PCIe, Ethernet, and TCP/IP
A can-do attitude to navigate through ambiguity and break complex challenges into solvable engineering problems

Responsibilities

Develop test methodology and specifications to verify and validate datacenter hardware against functional, performance and reliability requirements, in both development and production environments
Ensure accurate manufacturing and validation test coverage to collect design gaps in the development phase and screen out manufacturing assembly defects before they are shipped
Collaborate with Sourcing, NPI and Manufacturing teams to participate in supplier selection, define functional test coverage, pass/fail criteria, and manufacturing image features
Develop test stations to implement test coverage, which may include IQC, OQC, Randomized testing, Burn-In and REL
Own test preparation, authorize test methods, complete and oversee test executions to support validation tests at Lambda
Analyze test data and share learnings with Quality, Sourcing, NPI teams to enable FA/RCA and design countermeasures

Skills

Python

PCIe

Ethernet

TCP/IP

Oscilloscopes

Power Supplies

DMMs

Logic Analyzers

Signal Generators

Optical Test Equipment

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.

Land your dream remote job 3x faster with AI

Try Jobo Free