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San Jose, California, United States
Hybrid
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.
Hardware Engineering at Lambda is responsible for building and scaling the physical infrastructure powering all of Lambda's products. Our scope spans the full hardware lifecycle: roadmap and architecture, proof-of-concept for state-of-the-art platforms, new product introduction (NPI), and fleet-scale operations — all engineered for gigawatt-scale AI factories with rack-first design, advanced liquid cooling, and next-generation interconnects at the cutting edge of the industry. If you want your hardware work running at the frontier of AI compute, at a scale few teams in the industry operate at, this is that team.
What You’ll Do
Own system integration validation for new HPC AI/ML, general purpose compute, storage, and network hardware platforms throughout hardware NPI and deployment readiness.
Development and execution of functional, stress, reliability, error-injection and benchmark tests on new hardware systems. Enable automated tools for doing scale testing.
Collaborate with HPC deployment and operation teams, fleet engineering teams, infrastructure engineering and PMO teams to facilitate tooling automation and L10/L11/L12 level benchmarking throughout hardware NPI and at new hardware deployment.
Manage the firmware and software compatibility, track and recommend firmware and software releases during NPI, support HPC operation team on firmware and software maintenance after production release.
Support RMA team on critical hardware issues’ triage and Root-Cause-Analysis after deployment; own fleet hardware issues’ failure correlation, trend analysis, close the loop with Platform Hardware Engineer and Quality team to improve product reliability.
Own hands-on lab setup and test infrastructure for repeatable hardware evaluation, partnering with Platform Hardware Engineer, Data Center Engineering, and Cluster Network Design to ensure new platforms can be brought up, instrumented, stressed, benchmarked, and debugged consistently.
Manage hardware vendors regarding hardware validation and manufacturing testing; support new vendor evaluation and Quarterly Business Review on hardware vendors.
Drive alternate component qualification from technical evaluation through PLM enablement, develop and execute validation plans for key commodities such as memory, SSDs, NICs, PSUs, PDUs, fans, cables, optics, and transceivers.
You
5 years of experience in one or many of the following areas: hardware integration validation, fleet hardware reliability engineering, component qualification, performance validation for HPC, data center, or cloud infrastructure products.
Possess deep knowledge in system integration testing and performance benchmarking at one or many of the L10, L11 and L12 levels.
Experiences in validation of one or many of the following server hardware platforms: AI/ML, general compute (x86 and ARM), storage systems, or network switches.
Hands-on experiences with vendor-led product NPI cycles and can drive hardware validation, issues triage, debugging and root cause in both NPI and after production at scale.
Collaborate well across architecture, hardware and datacenter engineering, supply chain, fleet and infrastructure engineering, HPC deployments and operations, and vendor engineering teams to deliver complete, production-ready hardware solutions.
Strong ownership and can do attitude; self-starter who feels comfortable working in ambiguity.
Nice to Have
10+ years of experience in one or many of the following areas: hardware integration validation, fleet hardware reliability engineering, component qualification, performance validation for HPC, data center, or cloud infrastructure products.
Experience supporting AI/ML infrastructure and accelerated compute hardware (e.g., NVIDIA, AMD, Intel).
Experience in acceptance testing to enable large scale hardware deployments.
Deep knowledge in BMC, BIOS settings and network card configurations.
Proficient in validating, issue triaging, benchmarking and performance tuning for rack-scale servers at L10, L11, L12 levels.
Working knowledge of infrastructure toolings for asset management, provisioning, hardware lifecycle management, etc.
Working knowledge in PLM systems and BOM structure.
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.