3 months ago
Base Salary
$314k - $465k/yr
Responsibilities
- Design and implement a highly available and reliable GPU and CPU host and instance lifecycle control plane.
- Guide technical decisions involving semiconductor architecture, BIOS and firmware settings, system boot methods, and DPU utilization.
- Guide the design of the compute platform’s multi-tenant security model.
- Provide technical leadership and mentorship for senior engineers across several teams.
- Collaborate with product, data-center organizations, and customers to translate requirements into scalable infrastructure capabilities.
- Set engineering standards and lead design reviews for mission-critical cloud software at scale.
Requirements
- 10+ years of experience building compute control-plane distributed systems for deploying and lifecycle-managing heterogeneous compute platforms in data centers.
- Deep expertise in durable execution models and distributed systems used in cloud-service provisioning.
- Basic knowledge of software-defined networking fundamentals for secure, multi-tenant distributed systems.
- Proven experience leading large-scale semiconductor hardware enablement and deployment initiatives.
- Proven experience deploying new data centers into a global compute platform.
- Proficiency in one or more of C/C++, Rust, Python, or Go.
- Preferred knowledge of Nvidia AI Factory architecture, including GPU hosts, CPU hosts, SuperNICs, ConnectX, BlueField DPUs, and switches.
- Preferred knowledge of Nvidia AI Factory software, including DOCA, DOCA SNAP, and CUDA.
- Preferred knowledge of Linux kernel internals, device drivers, KVM, QEMU, SR-IOV, DPDK, and SPDK.
- Preferred experience with cloud service provider Kubernetes offerings.
- Preferred knowledge of InfiniBand, RoCE, and NVMe-oF.
Benefits
- Annual salary range is described, but no numeric base-pay amount is provided.
- 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.
- Requires presence in the Bellevue, San Francisco, or San Jose 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.