Simplify Logo

Full-Time

Manufacturing Quality Engineer

Confirmed live in the last 24 hours

Lambda

Lambda

51-200 employees

Cloud-based GPU services for AI training

Data & Analytics
Hardware
Enterprise Software
AI & Machine Learning

Compensation Overview

$120k - $180kAnnually

+ Cash Compensation + Equity Compensation

Senior, Expert

San Jose, CA, USA

Category
QA & Testing
Manual Testing
Quality Assurance
Requirements
  • Have a BS in Electrical, Computer, Industrial, or Mechanical Engineering or equivalent practical experience
  • 5+ years of manufacturing quality experience
  • Hold a deep understanding of AI, compute, storage, and/or networking hardware
  • Have previous experience in product development, manufacturing processes, quality practices and debug of compute, storage, network, and/or AI hardware
  • Are experienced in system (server) manufacturing and rack level integration
  • Have experience implementing manufacturing tests in an ODM/CM environment
  • Possess prior experience presenting performance metrics and quality trends to executive leadership
  • Are proficient in quality tools such as six sigma, statistical process control (SPC), and failure mode and effect analysis (FMEA)
  • Have knowledge of MES, PLM, and other supply chain/manufacturing software
Responsibilities
  • Ensure the quality of AI, compute, storage, network, and rack hardware that is deployed to Lambda’s data centers
  • Implement an ODM model to develop system and rack level hardware. Participate in the supplier selection process and drive bring up of manufacturing facilities and production lines
  • Implement a comprehensive QMS system to track quality throughout the lifecycle of a product. Set KPIs, audit manufacturing facilities, and generate quality scorecards to track supplier performance
  • Collaborate with sales, engineering, and supply chain to understand hardware configurations and manage the Bill of Materials (BOM)
  • Build end to end processes to manage the manufacturing process, including, but not limited to, customer requirements documentation (CRD), manufacturing test plans, and first article inspection (FAI) criteria
  • Partner with data center operations to drive the RMA process and work with suppliers to ensure proper root cause and corrective actions (RCCA)
  • Use statistical analysis to evaluate manufacturing processes to identify opportunities for improvement in efficiency, cost effectiveness, and product quality

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, 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.

Company Stage

Series C

Total Funding

$932.2M

Headquarters

San Jose, California

Founded

2012

Growth & Insights
Headcount

6 month growth

23%

1 year growth

67%

2 year growth

242%
Simplify Jobs

Simplify's Take

What believers are saying

  • Lambda Labs' competitive pricing and availability have attracted high-profile clients like Voltron Data, indicating strong market demand.
  • The recent $500M GPU-backed financing facility will enable Lambda to expand its cloud infrastructure significantly, enhancing service capabilities.
  • The appointment of Peter Seibold as CFO, with his extensive experience, is likely to strengthen Lambda's financial strategy and operational efficiency.

What critics are saying

  • The rising prices of AI cloud compute instances could deter cost-sensitive clients, impacting Lambda's customer acquisition.
  • The competitive landscape, with giants like AWS launching high-core instances, poses a threat to Lambda's market share.

What makes Lambda unique

  • Lambda Labs leverages NVIDIA's GH200 Grace Hopper™ Superchip, offering unmatched efficiency and price for AI training and inference, setting it apart from competitors.
  • Their Lambda Stack software simplifies AI-related software installation and upgrades, used by over 50,000 machine learning teams, providing a significant edge in user experience.
  • The Lambda Echelon service allows clients to take ownership of their infrastructure, a unique offering compared to traditional cloud service models.