Hardware Quality Engineer
Lambda is hiring a Hardware Quality Engineer. It pays $109k-$145k a year and Level rates it ; you can apply on Lambda.
Level's read on this job
- Little AI ●○○○ is how Level rates this role: aI is not part of the work.
- The posting allows some remote work.
- Tools and skills the posting cites include Qms, hardware quality and root cause analysis.
- Level classifies it as a senior role.
- Level lists 92 other open roles at Lambda.
AI in this role
Manage data center hardware quality issues and root cause analysis for AI cloud infrastructure.
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.
If you'd like to build the world's best AI cloud, join us.
*Note: This position requires presence in our San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.
The Operations team plays a critical role in ensuring the seamless end-to-end execution of our AI-IaaS infrastructure and hardware. This team is responsible for sourcing all necessary infrastructure and components, overseeing day-to-day data center operations to maintain optimal performance and uptime, and driving cross company coordination through product management organization to align operational capabilities with strategic goals. By managing the full lifecycle from procurement to deployment and operational efficiency, the Operations team ensures that our AI-driven infrastructure is reliable, scalable, and aligned with business priorities.
What You’ll Do
Track, log, and manage all quality issues arising in the data center during deployment and production environment
Perform root cause analysis (RCA) for every failure (hardware, software, process)
Analyze production system metrics and quality data to detect trends, anomalies, or weak points
Improve turnaround time (TAT) for Return Merchandise Authorization (RMA) processes
Design, monitor, and drive corrective and preventive actions (CAPA)
Implement and verify containment actions to keep systems operational until permanent fixes are applied.
Collaborate with operations, hardware, engineering, supply chain, and vendors to resolve quality issues
Capture and upload failure analysis (FA) reports and related data into Quality Management Systems (QMS)
Verify quality of spares (incoming and outgoing) to avoid repeat failures.
Define and track quality KPIs / SLAs and report on quality performance to leadership
Oversee MRB (Material Review Board) inventory, rework, disposal decisions
Ensure the quality management system (QMS) is up to date, with necessary training rolled out
Work cross-functionally during hardware ramp, deployments, and upgrades to ensure quality gates
Up to 30% travel may be required for this role.
You
Have experience working with hardware / data center / infrastructure systems
Are strong at data analysis, statistics, and metrics (you can turn raw data into insight)
Are skilled in root cause analysis methods (5 Whys, fishbone, 8D, A3, etc.)
Are comfortable managing cross-team communication, stakeholder expectations, and conflict resolution
Are detail-oriented, process-driven, and quality-minded
Have experience working with quality tools or QMS software (e.g. audit modules, ERP, defect tracking)
Communicate clearly in English (both written and verbal)
Nice to Have
Experience in the machine learning / AI infrastructure / GPU / HPC / computer hardware industry
Exposure to data center standards, certifications (e.g. ISO, Uptime Institute, etc.)
Experience working on vendor quality, supply chain quality, or incoming inspections
Understanding of firmware, embedded systems, reliability engineering
Familiarity with scripting or automation (Python, SQL, etc.) to help with data processing
Exposure to cloud or hyperscaler infrastructure operations
Experience with “manufacturing-like” quality concepts applied to compute hardware
Salary Range Information
The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
About Lambda
Founded in 2012, with 500+ employees, and growing fast
Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
Our values are publicly available: https://lambda.ai/careers
We offer generous cash & equity compensation
Health, dental, and vision coverage for you and your dependents
Wellness and commuter stipends for select roles
401k Plan with 2% company match (USA employees)
Flexible paid time off plan that we all actually use
Equal Opportunity Employer
Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
How we rate this
Hardware Quality Engineer at Lambda rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where hardware quality was part of your work. What did you do?
- Tell me about a project where root cause analysis was part of your work. What did you do?
- Tell me about a project where data center operations was part of your work. What did you do?
- Tell me about a project where capa was part of your work. What did you do?
- Walk me through how you've used Qms in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Hardware Quality, Root Cause Analysis, Data Center Operations, Capa, and Qms. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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