NVIDIA · 2 weeks ago
Principal Software Engineer – Large-Scale LLM Memory and Storage Systems
Washington, United States
Full-time
Onsite
Lead/Staff
$272K/yr - $431K/yr
15+ years expNVIDIA is a leading technology company known for its innovative work in AI and GPU technology. They are seeking a Principal Systems Engineer to define the vision and roadmap for memory management of large-scale LLM and storage systems, focusing on designing and evolving a unified memory layer for efficient LLM inference.
AI InfrastructureArtificial Intelligence (AI)Consumer ElectronicsFoundational AIGPUHardwareSoftwareVirtual Reality
Hiring Manager
Bushra S.
Responsibilities
Design and evolve a unified memory layer that spans GPU memory, pinned host memory, RDMA-accessible memory, SSD tiers, and remote file/object/cloud storage to support large-scale LLM inference
Architect and implement deep integrations with leading LLM serving engines (such as vLLM, SGLang, TensorRT-LLM), with a focus on KV-cache offload, reuse, and remote sharing across heterogeneous and disaggregated clusters
Co-design interfaces and protocols that enable disaggregated prefill, peer-to-peer KV-cache sharing, and multi-tier KV-cache storage (GPU, CPU, local disk, and remote memory) for high-throughput, low-latency inference
Partner closely with GPU architecture, networking, and platform teams to exploit GPUDirect, RDMA, NVLink, and similar technologies for low-latency KV-cache access and sharing across heterogeneous accelerators and memory pools
Mentor senior and junior engineers, set technical direction for memory and storage subsystems, and represent the team in internal reviews and external forums (open source, conferences, and customer-facing technical deep dives)
Qualification
Required
Masters or PhD or equivalent experience
15+ years of experience building large-scale distributed systems, high-performance storage, or ML systems infrastructure in C/C++ and Python, with a track record of delivering production services
Deep understanding of memory hierarchies (GPU HBM, host DRAM, SSD, and remote/object storage) and experience designing systems that span multiple tiers for performance and cost efficiency
Distributed caching or key-value systems, especially designs optimized for low latency and high concurrency
Hands-on experience with networked I/O and RDMA/NVMe-oF/NVLink-style technologies, and familiarity with concepts like disaggregated and aggregated deployments for AI clusters
Strong skills in profiling and optimizing systems across CPU, GPU, memory, and network, using metrics to drive architectural decisions and validate improvements in TTFT and throughput
Excellent communication skills and prior experience leading cross-functional efforts with research, product, and customer teams
Preferred
Prior contributions to open-source LLM serving or systems projects focused on KV-cache optimization, compression, streaming, or reuse
Experience designing unified memory or storage layers that expose a single logical KV or object model across GPU, host, SSD, and cloud tiers, especially in enterprise or hyperscale environments
Publications or patents in areas such as LLM systems, memory-disaggregated architectures, RDMA/NVLink-based data planes, or KV-cache/CDN-like systems for ML
Benefits
Equity
Benefits
Company
NVIDIA
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.
10001+ employees
H1B Sponsorship
NVIDIA has a track record of offering H1B sponsorships. Please note that this does not
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2025 (1877)
2024 (1355)
2023 (976)
2022 (835)
2021 (601)
2020 (529)
Funding
Current Stage
Public CompanyTotal Funding
$4.09BKey Investors
ARPA-EARK Investment ManagementSoftBank Vision Fund
2023-05-09Grant· $5M
2022-08-09Post Ipo Equity· $65M
2021-02-18Post Ipo Equity
Leadership Team
Jensen Huang
Founder and CEO
Michael Kagan
Chief Technology Officer
Recent News
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