Engineering Manager, Fleet Engineering
Lambda Labs
- Location
- San Francisco Office (Fremont St)
- Employment
- Full Time
- Work model
- Remote
- Level
- Mid
- Posted
- 4h ago
Skills
About this role
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