Lambda’s mission is to accelerate human progress with computation. Our Deep Learning workstations, servers, and cloud services power Machine Learning engineers at the forefront of Artificial Intelligence research, fueling advancements in quantum computing, cancer detection, autonomous aircraft, drug discovery, self-driving cars, and much more.

Lambda provides Artificial Intelligence and Machine Learning infrastructure to organizations like Intel, Microsoft, Amazon Research, Tencent, Kaiser Permanente, MIT, Harvard, Stanford, Caltech, and the Department of Defense.

Join us in building the future of Artificial Intelligence.

About the Role

As Lambda’s Head of High Performance Computing you will serve as Lambda’s most senior compute hardware engineer. You will lead and grow the team of engineers that design GPU-accelerated server and cluster products for deep learning engineers. In addition, you will perform technical work alongside the members of your team while collaborating with suppliers, customers, and other teams within Lambda.

What You’ll Do

  • Lead and grow Lambda’s high performance computing team.
    • Build a team that can design high-performance and cost-effective servers and clusters for deep learning.
    • Hire, develop, and retain world-class engineers.
    • Establish effective collaborations with customers, suppliers, and other teams within Lambda.
  • Provide technical expertise in high performance computing.
    • Design servers and clusters for deep learning.
    • Help your team members solve their thorniest technical problems.
    • Advise Lambda’s executive team on compute hardware.
    • Write internal and customer-facing technical content.
    • Stay up to date on the latest high performance computing technologies across compute, storage, networking, and software.
  • Be a member of Lambda’s technical leadership.
    • Develop ideas for new hardware products and features.
    • Participate in the development of Lambda’s overall technical strategy.
    • Reinforce Lambda’s positive culture throughout the organization.


  • Have extensive technical experience in high performance computing.
  • Have led a technical team.
  • Are skilled at hiring, retention, and professional development.
  • Build strong relationships across your entire organization.
  • Have many, but not necessarily all, of the following technical skills:
    • Linux system administration
    • High-performance network design
    • High-performance storage cluster design
    • Compute infrastructure for machine learning
    • GPU compute cluster design and manufacturing
    • GPU compute server design and manufacturing
    • Data center infrastructure
    • Technical writing
    • Customer requirement identification

Nice To Have

  • Experience in a customer facing role.
  • Hands on experience with machine learning.
  • A history of writing and speaking on technical topics.

About Lambda

  • We offer generous cash & equity compensation
  • Investors include Gradient Ventures, Google’s AI-focused venture fund
  • We are experiencing a high rate of growth and have 10x’d over the last 3 years
  • Our research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
  • We have a wildly talented team of 100, and are growing fast
  • Our remote workforce, based on role, is across the U.S., with headquarters in San Francisco
  • Health, dental, and vision coverage for you and your dependents
  • Commuter/Work from home stipends
  • 401k Plan
  • 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.