Job description

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, San Francisco, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. What You’ll Do - Architect and define scalable compute platforms optimized for AI/ML, simulation, and high-throughput workloads. - Develop compute system standards and design patterns to ensure consistency, performance, and maintainability across infrastructure. - Evaluate emerging CPU, GPU, and accelerator technologies, owning architectural tradeoff decisions that impact compute density, power, cooling, and total cost. - Collaborate with product and engineering teams to map workload requirements to compute platform capabilities across bare metal and cloud deployments. - Experience converting ambiguous business or customer needs into measurable platform requirements, technical specifications, acceptance criteria, and architecture decisions. - Define compute platform roadmaps and architectural reference designs that guide hardware selection, firmware baselines, rack-level, and cluster design. - Act as a technical lead during new platform introductions, guiding validation and performance characterization efforts. - Mentor systems engineers and cross-functional stakeholders on compute performance tuning, sizing, and architectural decisions. You - Proven experience (7+ years) architecting large-scale 10k-100k+ GPU HPC or cloud compute platforms. - Deep knowledge of CPU/GPU architectures, memory hierarchies, and accelerator topologies. - Experience designing systems around high-bandwidth, low-latency fabrics (NVLink, InfiniBand, and RoCE). - Strong understanding of system performance tuning, resource scheduling, thermal and power optimization, and compute lifecycle management. - Comfortable working across hardware and software boundaries, especially at the intersection of compute architecture, OS behavior, and orchestration layers. - Skilled at balancing architectural tradeoffs for density, power efficiency, cooling, and performance. - Strong analytical and communication skills, with a track record of influencing technical strategy across teams. - Strong ownership and can do attitude, self-starter who feels comfortable working in ambiguity. Nice to Have - Hands-on experience with AI/ML workloads and their compute performance characteristics. - Familiarity with orchestration tools used in HPC. (Slurm, Kubernetes, etc) - Experience with virtualization technologies, specifically GPU virtualization. - Exposure to hardware validation, vendor collaboration, and long-term OEM roadmap alignment. - Background in compute telemetry, real-time performance profiling, or large-scale A/B infrastructure testing. 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: lambda.ai - 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.

Requirements

Must-haves

If you'd like to build the world's best AI cloud, join us.
Note: This position requires presence in our San Jose, San Francisco, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.
What You’ll Do
Architect and define scalable compute platforms optimized for AI/ML, simulation, and high-throughput workloads.
Develop compute system standards and design patterns to ensure consistency, performance, and maintainability across infrastructure.
Evaluate emerging CPU, GPU, and accelerator technologies, owning architectural tradeoff decisions that impact compute density, power, cooling, and total cost.
Collaborate with product and engineering teams to map workload requirements to compute platform capabilities across bare metal and cloud deployments.
Experience converting ambiguous business or customer needs into measurable platform requirements, technical specifications, acceptance criteria, and architecture decisions.
Define compute platform roadmaps and architectural reference designs that guide hardware selection, firmware baselines, rack-level, and cluster design.
Act as a technical lead during new platform introductions, guiding validation and performance characterization efforts.
Mentor systems engineers and cross-functional stakeholders on compute performance tuning, sizing, and architectural decisions.
Proven experience (7+ years) architecting large-scale 10k-100k+ GPU HPC or cloud compute platforms.
Deep knowledge of CPU/GPU architectures, memory hierarchies, and accelerator topologies.
Experience designing systems around high-bandwidth, low-latency fabrics (NVLink, InfiniBand, and RoCE).
Strong understanding of system performance tuning, resource scheduling, thermal and power optimization, and compute lifecycle management.
Comfortable working across hardware and software boundaries, especially at the intersection of compute architecture, OS behavior, and orchestration layers.
Skilled at balancing architectural tradeoffs for density, power efficiency, cooling, and performance.
Strong analytical and communication skills, with a track record of influencing technical strategy across teams.
Strong ownership and can do attitude, self-starter who feels comfortable working in ambiguity.

Nice-to-haves

Hands-on experience with AI/ML workloads and their compute performance characteristics.
Familiarity with orchestration tools used in HPC. (Slurm, Kubernetes, etc)
Experience with virtualization technologies, specifically GPU virtualization.
Exposure to hardware validation, vendor collaboration, and long-term OEM roadmap alignment.
Background in compute telemetry, real-time performance profiling, or large-scale A/B infrastructure testing.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlkubernetesmachine learning

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Paid Time Off

Wellness