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aimlroles

Principal Software Engineer – Large-Scale LLM Memory and Storage Systems

NVIDIA nvidia.com Open · verified Nov 1, 2026
US, CA, Santa Clara Full-time Senior AI Engineering

At a glance

Senior AI Engineering role at NVIDIA. US, CA, Santa Clara · full-time · $272,000–$431,250 base.

SalaryStated by NVIDIA
$272,000 – $431,250
Base salary for this role, in USD per year, as published in the posting.
RoleAI Engineering
SenioritySenior
LocationUS, CA, Santa Clara
EmploymentFull-time
Base pay$272,000–$431,250
PostedOct 30, 2026 · 2d ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build a memory layer connecting GPU, host, RDMA-accessible, SSD and remote storage for large-scale LLM inference
  • Integrate LLM serving engines such as vLLM and SGLang to offload, reuse and share KV cache across clusters
  • Design protocols for disaggregated prefill and multi-tier KV-cache storage, including peer-to-peer sharing
  • Work with GPU, networking and platform teams to improve low-latency KV-cache access across memory pools
  • Set subsystem direction, mentor engineers and represent the team in reviews, conferences and technical discussions

What you bring

  • At least fifteen years building distributed, storage or ML infrastructure in C/C++ and Python, with production delivery experience
  • A master’s degree, PhD or equivalent experience
  • You understand multi-tier memory systems and have built distributed caches or key-value systems for low latency and high concurrency
  • You have hands-on experience with networked I/O and technologies such as RDMA, NVMe-oF or NVLink
  • You can profile CPU, GPU, memory and network performance, and lead cross-functional work with research, product and customer teams

Who this fits

This principal-level role suits an experienced systems engineer ready to set technical direction and mentor other engineers. You’ll focus on memory and storage for large-scale LLM inference, including KV-cache movement across memory tiers.

From the employer

NVIDIA Dynamo is a high-throughput, low-latency inference framework for serving generative AI and reasoning models across multi-node distributed environments. Built in Rust for performance and Python for extensibility, Dynamo orchestrates GPU shards, routes requests, and manages shared KV cache across heterogeneous clusters so that many accelerators feel like a single system at datacenter scale. As large language models rapidly outgrow the memory and compute budget of any single GPU, this platform enables efficient, resilient deployment of cutting-edge LLM workloads.


We are seeking a Principal Systems Engineer to define the vision and roadmap for memory management of large-scale LLM and storage systems.


What you'll be doing:

  • 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).

What we need to see:

  • 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.

Ways to stand out from the crowd:

  • 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.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our special engineering teams are growing fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you!

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Opportunity

AI Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

AI Engineering$270k+

Find me work

By the team behind aimlroles.

Find me work
Opportunity

AI Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind aimlroles.