Hardware Quality Engineer - Data Center

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)

- Strong understanding of Linux systems — able to troubleshoot, analyze logs, and debug hardware/software interactions.

- Hands-on experience working with server or data center hardware (GPUs, CPUs, NICs, DIMMs, power and cooling systems) and GPU clusters, InfiniBand, and RoCE-based interconnects

- Familiarity with root cause analysis (RCA) and Corrective & Preventive Actions (CAPA) processes.

- Experience managing and tracking hardware failures, RMAs, and quality issues using tools or QMS platforms.(e.g. audit modules, ERP, defect tracking)

- Ability to write and maintain simple scripts (Python, Bash, or SQL) for data collection, analysis, and automation.

- Strong analytical skills: comfortable using data to identify trends, anomalies, and reliability issues.

- Detail-oriented and process-driven mindset; able to document findings and follow through on corrective actions.

- Excellent communication skills: clear in writing and speaking, able to work across technical and non-technical teams.

- Willingness to travel to data centers (up to ~30%) for audits, inspections, and troubleshooting.

- 3+ years of experience in hardware quality engineering, reliability, or RMA operations within hyperscale or HPC environments.

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

A Final Note:

You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.

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.