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About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
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JOB TITLE: Senior Software Architect, AI Systems and Networking
The Senior Software Architect, AI Systems and Networking joins an applied research team within the Networking Systems & Software Architecture group to solve complex infrastructure problems for modern AI. This role involves owning modules end-to-end, from scoping research questions to shipping production code. Key responsibilities include architecting high-performance communication and memory management libraries, driving hardware-software co-optimization, and profiling data movement across GPU memory, system DRAM, NVMe, and network fabrics. The position requires expertise in C/C++, Rust, InfiniBand, RoCE, RDMA, NVLink, and GPUDirect. Candidates will integrate networking into AI serving stacks like vLLM, SGLang, and TensorRT-LLM. The work focuses on low-level transport optimization, communication frameworks, and emerging domains like quantum computing interconnects to move data between GPUs, nodes, and storage.
Architect and implement high-performance communication and memory management libraries for distributed AI.
Drive hardware-software co-optimization for GPUs, DPUs, NICs, and switches using RDMA and NVLink.
Profile and optimize data movement across GPU memory, system DRAM, NVMe, and network fabrics.
Integrate networking capabilities into AI serving stacks like vLLM, SGLang, and TensorRT-LLM.
Prototype experimental technologies to evaluate their viability for production AI infrastructure.
Own modules and projects end-to-end from initial research scoping to shipping production code.
Maintain open-source projects and conduct technical design reviews for the engineering team.
What we're looking for
12+ years in systems software and/or networking with demonstrated ownership of complex projects.
MS, PhD or equivalent experience in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Solid understanding of high-performance networking including InfiniBand, RoCE, RDMA, NVLink, and GPUDirect.
Strong C/C++/Rust systems programming with comfort in performance profiling and low-level debugging.
Understanding of ML systems concepts such as transformer architectures, KV cache mechanics, model parallelism, or distributed training and inference patterns.
Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements (preferred).
Knowledge of storage networking (NVMe-oF, GPUDirect Storage, S3) (preferred).
Background of Reinforcement Learning systems (preferred).
RDMA
RoCE
Python
C++
ASIC Design
Routing Protocols
Load Balancing
Congestion Control
Network Topologies
Real-time Software
Open Source
Accelerated Computing
CUDA
Python
C++
Rust
Deep Learning
Reinforcement Learning
TRT-LLM
SGLang
vLLM
Transformer Engine
GPU Programming
High-Performance Computing
Compilers
Inference Systems
Agentic AI
Multi-Agent Systems