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.
Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance.
What You’ll Do
Serve as the technical lead for integrating OEM and white-label compute, storage, and network hardware into Lambda’s HPC platform reference architectures.
Drive the end-to-end process of new product introduction (NPI) for hardware systems, including evaluation, validation, documentation, and production readiness.
Partner with architects to translate platform blueprints into concrete hardware selections and system configurations.
Work cross-functionally with design, engineering, operations, and vendor engineering teams to ensure compatibility, performance, and scalability of new systems.
Identify and resolve hardware issues across thermal, power, firmware, and mechanical domains during evaluation and bring-up cycles.
Provide technical guidance during vendor engagements and benchmarking of next-generation platforms.
You
Have 7+ years of experience in hardware integration or systems engineering for HPC, data center, or cloud infrastructure environments.
Possess deep knowledge of server hardware platforms (x86 and ARM), PCIe accelerators, storage devices, and network fabrics.
Are experienced with vendor-led product development cycles and can drive hardware evaluation, risk mitigation, and feedback into roadmap decisions.
Can interpret platform-level architecture requirements and select or adapt OEM solutions to fit.
Are comfortable working hands-on in labs with rack-scale deployments, BIOS/firmware tuning, and performance validation.
Collaborate well across architecture, design, engineering, and vendor teams to deliver complete, production-ready hardware solutions.
Nice to Have
Experience supporting AI/ML infrastructure and accelerated compute hardware (e.g., NVIDIA, AMD, Intel).
Familiarity with system thermals, power delivery, or integration at rack-scale.
Exposure to BMC/Redfish/IPMI configuration and automation.
Background in performance tuning, benchmarking, and systems validation workflows.
Prior experience contributing to reference designs or large-scale infrastructure blueprints.
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.
Top Skills
What We Do
Lambda provides computation to accelerate human progress. We're a team of Deep Learning engineers building the world's best GPU workstations and servers. Our products power engineers and researchers at the forefront of human knowledge. Customers include Microsoft, MIT, Los Alamos National Lab, Disney, Tencent, Kaiser Permanente, Stanford, Harvard, Caltech, and the Department of Defense.
