Senior Software Engineer - Fleet Engineering
Lambda Labs
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.Fleet Engineering at Lambda is responsible for logically deploying, provisioning, and maintaining our rapidly growing fleet, spanning GPU, CPU, and storage hosts along with the InfiniBand and networking fabric that ties them together.As a Senior Software Engineer in Fleet Engineering, you will build and improve the systems that take our clusters from hardware receiving through provisioning, configuration, and day-to-day operation in production. You will work on automation and tooling that keep the fleet consistent, healthy, and easy to operate as it grows. The systems you build directly determine how quickly and reliably new hardware turns into usable customer capacity.What You’ll DoFleet Engineering spans several teams. Depending on the team you join, your day-to-day will involve some combination of the following:Develop and Maintain Production Systems: Design, implement, and improve the software that powers fleet lifecycle management, machine configuration, and cluster state at scale.Automate Provisioning and Deployment: Build and enhance automation that takes clusters from logical design and racking through OS provisioning, configuration, validation, and customer hand-off.Support New Hardware and Site Bring-Up: Enable bring-up, validation, and production readiness for new server, accelerator, and network platforms, as well as new datacenter sites.Improve Machine Lifecycle Workflows: Refine bare metal provisioning, firmware and DPU updates, imaging, and system health monitoring across the fleet.Keep Fleet State Consistent and Healthy: Build systems that reconcile intended against actual configuration, catch drift before it causes deployment failures, and maintain production SLAs.Debug Hardware and Firmware Issues: Investigate failures across BIOS, BMC, firmware, DPUs, networking, storage, and boot flows.Collaborate Across Teams: Work closely with datacenter and deployment operations, networking, architecture, security, and product engineering teams to build scalable, maintainable solutions.YouHave 5+ years of engineering experienceAre fluent in Python, Go, or similar, and comfortable with APIs, distributed systems, and automation pipelinesWork confidently in Linux environments and can debug across the OS, hardware, and networking layersAre excited about working at the intersection of hardware, software, and physical datacenter buildsHave owned production systems with real SLAsCan lead technical design on medium-to-large features: take an ambiguous problem, write the doc, drive alignment across teams, and shipLeave systems, and the teammates around you, better than you found themNice to HaveExperience in AI or ML infrastructure, or other hyperscale compute environmentsHands-on experience with bare metal provisioning and lifecycle management, including technologies such as PXE, Redfish, IPMI, BMC, DHCP, and DNSFamiliarity with datacenter physical infrastructure, including racks, switches, InfiniBand fabric, and power domainsExperience diagnosing issues involving drivers, firmware, and hardware compatibility across GPU serversExperience with DPUs or programmable network acceleratorsExperience with network source-of-truth systems (NetBox or similar) or DCIM toolingExperience building Linux distributions or managing OS customization and imagingFamiliarity with Ansible or similar configuration management toolingExposure to Kubernetes and container orchestration conceptsExperience incorporating AI-assisted development tools into engineering workflows, including code generation, debugging, test development, and documentationIf you don’t meet all of these requirements but believe you may be a good fit, please still apply and provide a cover letter that helps us understand your experience and readiness for this role.Salary Range InformationThe 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 LambdaFounded in 2012, with 500+ employees, and growing fastOur 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 CoveWe have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOGOur values are publicly available: We offer generous cash & equity compensationHealth, dental, and vision coverage for you and your dependentsWellness and commuter stipends for select roles401k Plan with 2% company match (USA employees)Flexible paid time off plan that we all actually useEqual Opportunity EmployerLambda 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.Compensation Range: $230K - $395KLocationSan Francisco Office (Fremont St); Bellevue Office; San Jose Office (Zanker)Employment TypeFull timeLocation TypeHybridDepartmentData Center BusinessCompensationSan Francisco / San Jose$255K – $395KBellevue$230K – $356K
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