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NVIDIA • Shanghai, Shanghai, China
Role & seniority: Intern (compiler verification & testing) focusing on ML compiler tech.
Stack/tools: Python; modern C++; ML concepts (LLMs); familiarity with deep learning frameworks (PyTorch, Scikit-Learn, JAX/XLA, TensorRT); CUDA; Docker; GPU-Accelerated Cloud.
Verify new and state-of-the-art DL features and components against correctness and performance.
Implement verification programs, tools, scripts, and libraries.
Develop functional and performance tests and benchmarking solutions for compilers.
Enrolled in BS/MS/PhD in Computer Science, Computer/Electrical Engineering, Mathematics, or equivalent.
Strong Python programming skills.
Strong modern C++ programming skills.
Good understanding of machine learning concepts, including LLMs.
Experience with DL frameworks (PyTorch, Scikit-Learn, JAX/XLA, TensorRT).
Background in CUDA, Docker, or GPU-Accelerated Cloud.
Location & work type: Location not specified; Internship.
Do you want to help drive the progress of compilers for machine learning applications? Are you excited to learn how GPU performance powers technology such as mobile gaming, machine learning (ML), and self-driving cars? Are you passionate about challenging yourself and would you love to contribute as part of a world-class company? We are building the next generation of compiler technologies to accelerate ML workloads. We are looking for an intern to work on compiler verification & testing.
What You’ll Be Doing
In this role you will work closely with deep learning compiler developers to verify new and state of the art deep learning related features and components including implementing and executing functional and performance testing and benchmarking software solutions. This would include implementing verification programs, tools, scripts, and libraries. You will apply deep learning and other sophisticated techniques to implement compiler verification solutions.
What We Need To See
Pursuing BS/MS/PhD in Computer Science, Computer/Electrical Engineering, Mathematics or equivalent program. Strong Python programming skills Strong modern C++ programming skills Good understanding of machine learning domain and concepts, including Large Language Models (LLM)
Ways To Stand Out From The Crowd
Knowledge of deep learning frameworks such as Pytorch, Scikit Learn, JAX/XLA or TensorRT Background of other programming languages and domains such as CUDA, Docker and GPU-Accelerated Cloud
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