2 months ago
Base Salary
$266k - $395k/yr
Responsibilities
- Design, develop, and maintain scalable and reliable software for GPU/CPU compute infrastructure.
- Implement services for bare-metal and virtual machine instancing.
- Develop distributed systems to manage and orchestrate compute resources across multiple SKUs.
- Build workflows for compute instance lifecycles, system health, host validation, and cluster validation.
- Contribute to internal platform tooling and improve software delivery workflows.
- Troubleshoot and debug complex production and development issues across software, infrastructure, and vendor systems.
- Participate in on-call support and own incidents.
- Collaborate across engineering teams and drive resolution of ambiguous requirements and solutions through RFCs.
Requirements
- 5+ years of production experience with Go or Python.
- 5+ years of experience with bare-metal and virtualization hardware management and configuration.
- Comfort working in Linux environments and debugging at the operating-system, hardware, and networking layers.
- Ability to independently troubleshoot complex systems and communicate across software, infrastructure, and vendor teams.
- Preferred experience with GPU infrastructure or high-performance computing environments.
- Preferred experience with Slurm or Kubernetes-based cluster management.
- Preferred experience with public cloud internals, virtualization, KVM, QEMU, security, and fleet health.
- Preferred experience with durable execution platforms such as Temporal.
Benefits
- Annual salary range information is provided, but no numeric range is stated.
- Generous cash and equity compensation.
- Health, dental, and vision coverage for employees and dependents.
- Wellness and commuter stipends for select roles.
- 401(k) plan with a 2% company match for USA employees.
- Flexible paid time off plan.
- Requires presence in the San Francisco, San Jose, or Bellevue office four days per week, with Tuesday designated as the work-from-home day.
About Lambda
Lambda provides GPU cloud computing and on-prem AI hardware—servers, clusters, and workstations—for teams training and serving large ML models. Its products include NVIDIA H100/A100 instances, managed clusters, and the Lambda Stack software, sold via usage-based cloud pricing and hardware sales. Founded in 2012 and headquartered in San Francisco, the privately held company serves researchers, startups, enterprises, and hyperscalers.