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Software Engineer - Fleet

Role overview

Qualifications

  • 2+ years of experience with Go (Golang) or Python in production environments
  • 2+ years of experience with configuration management tools and practices
  • Comfortable working in Linux environments and debugging issues at the OS, hardware, and networking layers
  • Independently troubleshoot complex systems and communicate effectively across software, infrastructure, and vendor teams

Responsibilities

  • Develop and maintain production systems powering GPU fleet lifecycle management and machine configuration at scale
  • Automate infrastructure: Build and enhance automation frameworks for machine provisioning, configuration management, and deployment
  • Support New Hardware Introduction (NPI): Enable bring-up, validation, and production readiness for new server and accelerator platforms
  • Enhance machine lifecycle processes: Improve workflows for bare metal provisioning, firmware updates, and system health monitoring

About the company

Lambda logo

Lambda

The Superintelligence Cloud | Gigawatt-scale AI Factories for Training & Inference

Company details

Company size201 - 500

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Job description

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 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 cloud console, APIs, and systems, as well as internal tooling for system deployment, management, and maintenance.

What You’ll Do

  • Develop and Maintain Production Systems: Design, implement, and improve software that powers GPU fleet lifecycle management and machine configuration at scale.

  • Automate Infrastructure: Build and enhance automation frameworks for machine provisioning, configuration management, and deployment.

  • Support New Hardware Introduction (NPI): Enable bring-up, validation, and production readiness for new server and accelerator platforms.

  • Enhance Machine Lifecycle Processes: Improve and refine workflows for bare metal provisioning, firmware updates, and system health monitoring.

  • Debug Hardware and Firmware Issues: Investigate failures across BIOS, BMC, firmware, networking, storage, and boot flows.

  • Collaborate Across Teams: Work closely with infrastructure, security, and product engineering teams to develop scalable and maintainable solutions.

You

  • Have 2+ years of experience working with Go (Golang) or Python in production environments.

  • Have 2+ years of experience with configuration management tools and practices.

  • Are comfortable working in Linux environments and debugging issues at the OS, hardware, and networking layers.

  • Can independently troubleshoot complex systems and communicate effectively across software, infrastructure, and vendor teams.

Nice to Have

  • Experience with Go in infrastructure, systems, or backend development.

  • Hands-on experience with bare metal provisioning and lifecycle management, including technologies such as Redfish, BMC, IPMI, DHCP, and PXE.

  • Experience diagnosing issues involving drivers, firmware, and hardware compatibility across GPU servers.

  • Experience incorporating AI-assisted development tools into engineering workflows, including code generation, debugging, test development, and documentation.

  • Experience building Linux distributions or managing OS customization and imaging.

  • Familiarity with Ansible for system configuration and automation.

  • Exposure to Kubernetes and container orchestration concepts.

If 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 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.

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Marcus Rivera

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