Engineering Manager, HPC Deployments

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 Francisco/San Jose or Bellevue 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.

About the Role

Engineering at Lambda is responsible for building, operating, scaling and maintaining our AI Cloud offerings. The HPC Deployments team are responsible for deploying cutting edge NVIDIA GPU clusters on time, at scale and with 100% quality & correctness.

Reporting to the Director of Fleet Engineering, you will lead and scale one of our HPC Deployments teams. This work is highly cross functional and critical to the timely success of our customers. Your team is focused on building and validating clusters deployed across our data center facilities. You will work collaboratively with Product and Infrastructure engineering teams to improve transparency, metrics, automation and overall efficiency for the team.

We value diverse backgrounds, experiences, and skills, and we are excited to hear from candidates who can bring unique perspectives to our team. If you do not exactly meet this description but believe you may be a good fit, please still apply and help us understand your readiness for this Manager role. Your application is not a waste of our time.

What You’ll Do

• Lead and grow a distributed top-talent team of HPC engineers responsible for the configuration, validation, deployment of large scale GPU clusters.

• Work cross functionally with teams in the organization to deliver projects and deployments on time, ensuring alignment across stakeholders.

• Identify opportunities for efficiency improvements in the tools / process / automation that the team relies upon day to day.

• Ensure stakeholders have clear visibility into deployment progress, risks, and outcomes.

• Drive outcomes by managing staff allocations, project priorities, deadlines, and deliverables.

• Conduct regular one-on-one meetings, provide constructive feedback, and support career development for team members.

• Stay current on the latest HPC/AI technologies and best practices

• Participate in the qualification efforts of new technologies for use in our production deployments

You

• Extensive experience in HPC or large-scale infrastructure, including at least 3 years in a leadership or management role.

• Work well under deadlines and structured project plans; able to successfully (and tactfully) negotiate changes to project timelines

• Have excellent problem solving and troubleshooting skills

• Can effectively collaborate with peer engineering managers to coordinate efforts that may impact deployment operations

• Are comfortable leading and mentoring HPC engineers on cluster deployments as needed

• Experience building a high-performance team through deliberate hiring, upskilling, planned skills redundancy, performance-management, and expectation setting.

• Have flexibility to travel to our North American data centers as on-site needs arise or as part of training exercises

Nice to Have

• Experience with Linux systems administration, automation, scripting/coding.

• Experience with containerization technologies (Docker, Kubernetes)

• Experience working with the technologies that underpin our cloud business (GPU acceleration, virtualization, and cloud computing)

• Experience with machine learning and deep learning frameworks (PyTorch, Tensorflow) and benchmarking tools (DeepSpeed, MLPerf)

• Soft Skills (customer awareness, diplomacy)

• Bachelor’s degree or equivalent experience in a technical field.

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

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.