Lambda

Staff HPC Systems Architect

Lambda$160K — $190K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years of experience architecting large-scale GPU HPC or cloud compute platforms.
  • Deep knowledge of CPU/GPU architectures, memory hierarchies, and accelerator topologies.
  • Experience in designing systems around high-bandwidth, low-latency fabrics.
  • Strong understanding of system performance tuning and compute lifecycle management.
  • Ability to operate across hardware and software boundaries, understanding OS behavior and orchestration layers.
  • Skilled at making architectural trade-offs regarding density and power efficiency.
  • Excellent analytical and communication skills, with a proven influence on technical strategy.

Responsibilities

  • Architect scalable compute platforms for AI/ML and high-throughput workloads.
  • Develop standards and design patterns for system consistency and performance.
  • Evaluate emerging technologies and make architectural trade-offs affecting compute efficiency.
  • Collaborate with teams to align workload requirements with compute capabilities.
  • Translate ambiguous business needs into technical specifications and architectural decisions.
  • Define platform roadmaps and architectural designs for hardware and cluster selection.
  • Lead validation and performance characterization efforts for new platform introductions.

Benefits

  • Generous cash & equity compensation packages.
  • Health, dental, and vision coverage for employees and dependents.
  • Wellness and commuter stipends available for specific roles.
  • 401k plan with a 2% company match for US employees.
  • Flexible paid time off plan that is actively encouraged for use.
Full Job Description
*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.

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

About Lambda

Lambda is an online education company that offers courses in computer science and software engineering. The company was founded in 2017 by Austen Allred and Ben Nelson. Lambda's courses are designed to be accessible to anyone, regardless of their background or prior experience. The company's mission is to provide high-quality education that leads to well-paying jobs in the tech industry. Lambda has partnerships with a number of companies, including Amazon, Google, and Microsoft, and has helped thousands of students launch careers in tech.
Learn more about Lambda
Size
1,000 employees
Industry
Net Income
-$5 million
Founded
2017
5 Year Trend
+100%
Revenue
$100 million
NASDAQ

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