Systems Quality and Reliability Lead
GroqSalary not specified
- Full Time
- Senior (5 to 8 years)
$100,000 – $130,000Compensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Hardware, Industrial & ManufacturingIndustries
Requirements
Candidates should have experience with Python scripting for QA automation and improvement, along with hands-on experience with PXE server management and deployment. They must be skilled in GPU stress testing, CPU performance testing, and hardware validation techniques. A keen understanding of hardware manufacturing processes and quality assurance methodologies is essential, as is the ability to create detailed documentation for validation procedures and outcomes. Familiarity with ISO standards, regulatory compliance, and industry best practices is required, along with excellent analytical, problem-solving, and troubleshooting skills. Effective communication and the ability to work well in cross-functional teams are also necessary.
Responsibilities
The Manufacturing QA Hardware Validation Engineer will develop, implement, and maintain QA processes specific to hardware manufacturing. They will perform comprehensive hardware validation, including functional, performance, stress, and environmental testing. The role involves writing and maintaining scripts to automate and improve QA testing processes, managing PXE server setups for hardware deployment and testing environments, and conducting GPU stress testing and CPU performance evaluations. They will create detailed documentation for all hardware validation processes and outcomes, collaborate with design, engineering, and production teams to identify and resolve product issues, oversee quality standards across the supply chain, conduct failure analysis, recommend corrective actions, perform regular audits of manufacturing processes, and drive root cause analysis for production issues.
Skills
Python
PXE Server
GPU Stress Testing
CPU Performance Testing
Hardware Validation
Scripting
QA Automation
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.
Key Metrics
San Jose, CaliforniaHeadquarters
2012Year Founded
$372.6MTotal Funding
DEBTCompany Stage
AI & Machine LearningIndustries
201-500Employees