Software Engineering Intern, DLFW Comms

NVIDIA

. Integrate new communication library features into AI frameworks from proof of concept through performance analysis to production .

Posted 9/20/2026full-timeShanghai • ChinaEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI frameworks and communication library integration, with a strong focus on kernel authoring and performance optimization on NVIDIA platforms. Proficient in rapid prototyping and development using Python, C++, and CUDA, with a solid understanding of large-scale AI workloads and models.

Highest-signal resume keywords

Kernel AuthoringCUDA OptimizationAI FrameworksPython DevelopmentMulti-GPU Communication

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Applicant Tracking System Keywords

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Hard Skills

CUDAC++PythonTritonCuTePyTorchJAXTRT-LLMVLLMSGLang

Soft Skills

AdaptabilityEffective CommunicationCollaboration

Tools & Technologies

NVIDIA PlatformsAI ModelsPerformance Analysis

Industry Keywords

AI WorkloadsLarge-Scale TrainingProduction InferenceDeep Learning Communication PatternsExpert Parallelism

Tech Stack

Tools & technologies

PythonPyTorchC++

About the role

Key responsibilities & impact

Integrate new communication library features into AI frameworks from proof of concept through performance analysis to production
Analyze AI workloads and frameworks to identify multi-GPU communication requirements and opportunities
Collaborate hands-on with teams working on the latest AI models
Author custom communication or fused compute-communication kernels for maximum performance on NVIDIA platforms
Conduct in-depth research to achieve SOL GPU performance
Build fault-tolerant and elastic solutions for large-scale or dynamic AI workloads
Collaborate with a dynamic team across multiple time zones

Requirements

What you’ll need

Pursuing an M.S. or Ph.D. in CE/CS/EE
Strong background in communication, kernel authoring, and/or AI training/inference
Rapid prototyping and development with Python, C++, CUDA, or related DSLs such as Triton and cuTe
Solid understanding of LLM models and parallelisms
Adaptability and passion to learn new areas and tools
Flexibility to work and communicate effectively
Development experience with PyTorch, JAX, TRT-LLM, vLLM, SGLang, or veRL is advantageous
Experience with DL communication patterns such as Expert Parallelism (EP), TP, DP, and PP is advantageous
Experience with CUDA kernel optimization and profiling is advantageous
Experience with large-scale training or production inference stack is advantageous

Benefits

Comp & perks

Highly competitive salaries
Comprehensive benefits package
Benefits for employees and their families