Staff Software Engineer - Compute

The role

You will define the technical vision for the next-generation GPU and CPU host instance lifecycle and compute control plane. You will provide technical leadership to build and optimize GPU-first compute systems and manage a heterogeneous compute platform at scale.

What you will do

• Designing and implementing a highly available and reliable GPU and CPU host and instance lifecycle control plane.
• Guide technical decisions involving semiconductor architecture, BIOS/Firmware settings, system boot methodologies, and DPU utilization.
• Guide design of compute platform multi-tenant security model.
• Provide technical leadership and mentorship for senior engineers.
• Collaborate with product and data center organizations to translate customer requirements into scalable infrastructure capabilities.
• Work with customers on translating vague customer technical requirements into concrete engineering deliverables.
• Set engineering standards and lead design reviews for mission-critical cloud software at scale.

Required qualifications

• 10+ years of experience working on compute control plane distributed systems used for deploying and lifecycle managing heterogeneous compute platforms into data-centers.
• Deep expertise in durable execution models and distributed systems used in cloud-service provisioning.
• Basic knowledge of software defined networking fundamentals that informs secure, multi-tenant distributed systems.
• Proven track record of leading large-scale semi-conductor hardware enablement and deployment initiatives.
• Proven experience in deploying net-new data-centers into a global compute platform.
• Proficiency in one of more of the following programming languages: C/C++, Rust, Python, Go.

Nice to have

• Knowledge of Nvidia’s AI Factory architectural components (including GPU hosts, CPU hosts, SuperNICs (ConnectX and Bluefield DPUs , and switches).
• Knowledge of Nvidia’s AI Factory software offerings (like DOCA, DOCA SNAP, CUDA, et al.)
• Knowledge of Linux kernel internals, device drivers, and virtualization technologies (KVM, QEMU), kernel bypass technologies (like SR-IOV, DPDK, SPDK).
• Experience with Cloud Service Provider Kubernetes offerings.
• Knowledge of high-performance networking (InfiniBand, RoCE) and storage protocols (NVMe-oF).

Benefits

• 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

About the company

Lambda is a leader in AI cloud infrastructure serving tens of thousands of customers. Founded in 2012, the company has 500+ employees and is growing fast.