16 days ago
Base Salary
$314k - $465k/yr
Responsibilities
- Set technical direction for storage software architecture across petabyte-scale deployments.
- Author and review design documents, mentor senior engineers, and serve as the technical anchor for cross-functional storage initiatives.
- Design, develop, and maintain high-performance storage systems across file, block, and object protocols.
- Build distributed systems for storage-resource orchestration and integrate with NVMe, GPU-direct, and DPU-accelerated hardware.
- Own storage software through requirements, design, deployment, monitoring, maintenance, benchmarking, profiling, and capacity planning.
- Troubleshoot production issues involving performance, protocols, hardware, and failure domains.
- Partner with networking, control plane, Kubernetes, observability, compute, and fleet engineering teams.
- Define and track storage SLOs and SLIs and support reliable deployment and maintenance of distributed storage infrastructure.
- Evaluate emerging storage protocols and hardware and optimize infrastructure for AI training, checkpoint I/O, dataset serving, and inference workloads.
Requirements
- 10+ years of experience in storage systems engineering.
- 5+ years in a technical lead or Staff+ individual contributor role.
- Proven experience designing and operating multi-petabyte storage infrastructure in production data-center or cloud environments.
- Background in HPC, AI/ML infrastructure, or large-scale cloud storage.
- Strong proficiency in C, C++, Rust, or Go and the ability to write high-performance concurrent production systems code.
- Hands-on production experience with at least two object, block, or file storage protocols, including implementing or maintaining protocol servers or clients.
- Experience profiling and tuning throughput, latency, and IOPS using tools such as fio or elbencho.
- Working knowledge of NVMe, NVMe-oF, RDMA, RoCE or InfiniBand, and DPUs.
- Experience with physical data-center environments, rack-scale infrastructure, storage hardware, reliability design, runbooks, and incident response.
- Familiarity with Prometheus, Grafana, log aggregation, and tracing for storage observability.
- Preferred experience with NVIDIA BlueField DPUs or SuperNICs, GPUDirect Storage, Vast Data, Weka, NetApp, Lustre, Ceph, CXL memory pooling, computational storage, ZNS SSDs, or open-source storage projects such as DAOS and MinIO.
Benefits
- The role requires working from the San Francisco or Bellevue office four days per week, with Tuesday designated as the work-from-home day.
- Generous cash and equity compensation are offered.
- Health, dental, and vision coverage are provided for employees and dependents.
- Wellness and commuter stipends are available for select roles.
- A 401(k) plan with a 2% company match is available to USA employees.
- Flexible paid time off is offered.
Tech Stack
Categories
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.