Software Engineer - Compute

We are seeking a Software Engineer with good experience in backbone infrastructure that build, scale and optimize GPU-first cloud infrastructure that enables High Performance Computing and demanding AI workloads. In this role you will be responsible for:

• Design, develop and maintain software for GPU/CPU compute infrastructure with focus on performance, scalability, and reliability.
• Implement and develop services for baremetal and VM instancing.
• Develop distributed systems for managing and orchestrating compute resources across various SKU’s.
• Troubleshoot and debug complex issues in a production and development environment.
• On-call and incident ownership
• Collaboration across multiple teams and drive ambiguity in requirements or solutions on RFC’s.

• 3+ years of experience working with Go (Golang) or Python in production environments.
• 3+ years of experience with bare metal & virtualization hardware management and configuration.
• 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.

• Familiarity with GPU Infrastructure or high-performance computing environments.
• Experience with Slurm or Kubernetes-based cluster management.
• Experience with core public cloud internals (Virtualization, KVM, QEMU, Security and Fleet health)
• Experience with durable execution platforms like Temporal.

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.

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.

The Compute Software Engineering role plays a key part in the foundation of both the Public and Private Cloud offerings by enabling Bare-Metal and Virtual Machine provisioning. In this role you will: Develop and integrate workflows for compute instance lifecycle, system health, host and cluster validation, and contribute to and evolve the internal platform tooling, and workflows. As part of the Compute Engineering team, this position focuses on improving the bare-metal and VM developer and customer experiences, streamlining the software delivery lifecycle, building, testing, and shipping software efficiently and reliably.

The position works closely with various engineering teams across the company and contributes directly to Lambda’s ability to scale engineering productivity, maintain high delivery velocity, and support the company’s continued growth by making the right engineering workflows easier, faster, and more reliable.

• 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