Senior Architect - NIXL Adoption in China

Inference has become a networking problem. With disaggregated serving, where prefill runs on one set of GPUs, decode on another, and KV cache streams between them, performance depends on how fast you can move tensors between GPUs, across nodes, and in and out of storage.

We are hiring a senior architect to work directly with the platform teams building some of the world's most demanding inference deployments in China, understanding what breaks at scale and turning that into upstream code and roadmap. You will work daily with core NIXL and Dynamo engineers in Israel and the US.

Responsibilities:

• Drive NIXL adoption in China, from the first architecture conversation through prototype and benchmark to production rollout and upstream contribution.
• Profile customer inference stacks and fix what's costing throughput and TTFT: KV cache movement, memory registration, transfer scheduling.
• Write NIXL backends and plugins, extend Dynamo integrations, and contribute optimizations upstream to NIXL and GPUDirect class data paths.
• Help define the APIs that make the data path dynamic, supporting elastic scaling, worker churn and runtime rerouting in production inference clusters.
• Bring the region's requirements into NVIDIA's roadmap with enough technical authority to change it.
• Grow the local community around NIXL through talks, benchmarks and reference architectures.

Requirements:

• M.Sc. or Ph.D. in CS/EE/CE, or equivalent depth earned in industry.
• 12+ years building or optimizing large scale distributed systems: AI inference or training infrastructure, communication libraries, high performance networking, or HPC runtimes.
• Strong systems programming in C++ and Python, with performance critical code shipped.
• Hands on experience with RDMA networking (InfiniBand or RoCE) and GPU memory movement.
• Working knowledge of modern LLM serving, including prefill/decode disaggregation, KV cache management, tensor and pipeline parallelism, and at least one serving stack (Dynamo, TensorRT-LLM, vLLM, SGLang, Triton).
• Strong communication skills, with the technical credibility to be taken seriously by customer engineering teams and by NVIDIA's core library maintainers.
• Fluent Mandarin and professional English, and comfortable working across China, Israel and US time zones.

Preferred Qualifications:

• Open source contributions to NIXL, Dynamo, NCCL, vLLM, SGLang, TensorRT-LLM or Mooncake.
• Inference at genuine scale: thousands of GPUs, multi tenant clusters, strict SLOs.
• CUDA, and comfort reading kernel and driver level code when the answer is down there.
• A community you've built: a project people adopted, a talk people still cite.