About this role
Lambda is seeking a Hardware Quality Engineer to join the Data Center Business team in San Jose, operating on a hybrid schedule with remote flexibility. This full-time position is ideal for a detail-oriented professional with a strong background in hardware and data center systems who wants to build the world's best AI cloud infrastructure.
Role Overview
The Operations team at Lambda ensures the seamless end-to-end execution of AI-IaaS infrastructure and hardware. As a Hardware Quality Engineer, the chosen candidate will manage data center quality issues, drive continuous improvement, and ensure that AI-driven infrastructure remains reliable and scalable.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
About the Company
Founded in 2012, Lambda has grown rapidly with over 500 employees and backing from notable investors and industry leaders like NVIDIA, SK Group, and leading venture firms. The company builds AI cloud infrastructure serving tens of thousands of customers ranging from independent AI researchers to massive hyperscalers, with research papers accepted at top machine learning and graphics conferences.
How to Apply
Interested candidates should submit their application directly on the official company careers page.
Skills and tech stack
Questions candidates ask
What is the location and work arrangement for this role?
This position is based in the San Jose office, requiring physical presence 4 days per week with Tuesday designated as a work-from-home day.
What is the salary range for the Hardware Quality Engineer position?
The annual salary range is set between $109,000 and $145,000 USD, depending on qualifications.
What travel is required for this position?
Up to 30% travel may be required for this role.
What kind of benefits does Lambda offer?
Lambda offers cash and equity compensation, health, dental, and vision coverage, wellness and commuter stipends for select roles, a 401(k) plan with a 2% company match, and flexible paid time off.
What are the core technical requirements for applicants?
Applicants need experience with hardware or data center infrastructure systems, strong data analysis and statistics skills, proficiency in root cause analysis methods, and familiarity with QMS software or ERP tools.
