Lambda
Overview
Lambda, The Superintelligence Cloud, builds Gigawatt-scale AI Factories for Training and Inference. Lambda’s mission is to make compute as ubiquitous as electricity and give every person access to artificial intelligence. One person, one GPU. If you'd like to build the world's best deep learning 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. 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, ~400 employees (2025) and growing fast
We offer generous cash & equity compensation
Our investors include Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, US Innovative Technology, Gradient Ventures, Mercato Partners, SVB, 1517, Crescent Cove.
We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitability
Our research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
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.
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Lambda, The Superintelligence Cloud, builds Gigawatt-scale AI Factories for Training and Inference. Lambda’s mission is to make compute as ubiquitous as electricity and give every person access to artificial intelligence. One person, one GPU. If you'd like to build the world's best deep learning 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. 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, ~400 employees (2025) and growing fast
We offer generous cash & equity compensation
Our investors include Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, US Innovative Technology, Gradient Ventures, Mercato Partners, SVB, 1517, Crescent Cove.
We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitability
Our research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
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.
#J-18808-Ljbffr