Lambda · San Francisco
OtherData Center BusinessRemoteFullTimeposted 2w ago
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.
About the Role
Fleet Engineering owns the full lifecycle of Lambda's production systems infrastructure — new product introduction, deployment, operation, and reliability of our GPU fleet. We enable the building and running of that infrastructure with speed, ease, and quality. The Fleet Engineering teams:
HPC Deployments — Turns bare metal into production-ready capacity: ensure firmware leveling, system burn-in to shake out early failures, and validation of server performance and correctness, through to the InfiniBand fabric and GPU clusters.
Fleet Reliability — Day-2 operations across the fleet. Keeps systems healthy and keeps as much of the fleet in service for as much of its useful life as possible.
Fleet Orchestration / Data — Owns our production source of truth system. Synchronizes data from upstream systems and holds the line on correctness and quality, because everything automated downstream depends on it.
Fleet Orchestration / Automation — Owns the workflow orchestration system which people use to safely work on fleet systems for workflows that include: locking hosts, running firmware leveling jobs, OS installs, burn-in and validation, and reporting on work in flight and its results.
Fleet Foundation — Builds the host enablement tooling systems: OS and ZTP switch provisioning, firmware management, out-of-band access, and power management.
The work is highly cross-functional, carries executive visibility, and has a direct impact on Lambda and our customers. Fleet Engineering is at the forefront of delivering on-time, high-quality GPU capacity while driving efficiency at scale.
We are hiring multiple Engineering Managers for the following teams: Fleet Reliability, HPC Deployments, Fleet Foundation, Fleet Orchestration / Automation. This is a single application for all of them: you apply once, we get to know you, and we match you to the team where your strengths land best.
We value diverse backgrounds, experiences, and skills, and we're excited to hear from candidates who bring a unique perspective. If you don't exactly meet this description but believe you may be a good fit, please still apply and help us understand your readiness for this role. Your application is not a waste of our time.
What You'll Do
Lead and grow a distributed team of top-talent engineers responsible for the deployment and operation of production systems infrastructure.
Work cross-functionally to deliver projects and deployments on time, ensuring alignment across stakeholders.
Identify opportunities for efficiency gains in the tools, processes, and automation that teams across the organization rely on day to day.
Give stakeholders clear visibility into project progress, risks, and outcomes.
Participate in qualification efforts for new technologies entering our production deployments.
Drive outcomes by managing staff allocation, project priorities, deadlines, and deliverables.
Hold regular 1:1s, give constructive feedback, and support career development for your team.
Contribute to reliability through participation in our Incident Management and Review programs.
You
Have 3+ years leading or managing engineers, in AI/ML infrastructure or another large-scale compute environment.
Have owned production systems with real SLAs, and can balance keeping things running against long-term, high-impact work — paying down toil and technical debt along the way.
Work confidently in Linux and can debug across the OS, hardware, and networking layers.
Can lead technical design on medium-to-large efforts: take an ambiguous problem, write the doc, drive alignment across teams, and ship.
Work well under deadlines and structured project plans, and can tactfully negotiate changes to timelines when reality demands it.
Collaborate effectively with peer engineering managers on efforts that cut across deployment and operations.
Build high-performing teams deliberately — through hiring, upskilling, planned skills redundancy, performance management, and clear expectations.
Have excellent problem-solving and troubleshooting instincts.
Are excited about working at the intersection of hardware, software, and physical datacenter builds.
Leave systems, and the teammates around you, better than you found them.
Nice to Have
Depth in any one of these is a strong signal, and helps us place you on the right team. Nobody has all of them.
Linux systems administration, TCP/IP networking, automation, and scripting.
Bare metal provisioning and lifecycle management — PXE, Redfish, IPMI, BMC, DHCP, DNS.
Strong coding ability in at least one language, plus comfort with APIs, distributed systems, and automation pipelines.
The technologies underpinning our cloud business: GPU acceleration, virtualization, cloud computing.
Datacenter physical infrastructure: racks, switches, InfiniBand fabric, power domains.
Network source-of-truth or DCIM tooling (NetBox or similar), and data quality practice at scale.
Building Linux distributions, or managing OS customization and imaging.
Incorporating AI-assisted development tools into engineering workflows — code generation, debugging, test development, documentation.
Customer awareness, empathy, and 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
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.