Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
CUDA
Communication @ 6
Deep Learning @ 7
GPU
GitHub
JAX @ 7
Performance Analysis
PyTorch @ 7
Python @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Join us at the forefront of AI compiler technology and help shape the future of accelerated computing. NVIDIA is seeking passionate engineers to build the next generation of tools used by AI developers and researchers worldwide. Our team is developing Thunder, an ambitious, source-to-source compiler built to unlock outstanding performance for PyTorch models on NVIDIA GPUs. This is a unique opportunity to contribute to a project that enhances the PyTorch ecosystem, working with modern compiler stacks like PyTorch 2.0's TorchDynamo and TorchInductor to create powerful, open-source solutions that benefit the entire community. If you are driven to solve complex problems and want to make a foundational impact on the AI ecosystem, apply to join our collaborative and innovative team.
Responsibilities
- Lead the design, implementation, optimization, and maintenance of core compiler technologies that accelerate massive deep learning workloads.
- Perform performance analysis by scrutinizing workloads running on thousands of GPUs to find optimization opportunities that will shape the future design of Thunder.
- Collaborate with engineers who built PyTorch for NVIDIA hardware and help pioneer new features and stay at the forefront of framework development.
- Work closely with compiler, library, and systems teams—including experts behind nvFuser, TVM, XLA, and CUDA—to translate the latest research into practical, high-impact solutions for the open-source community.
Requirements
- Bachelor’s, Master’s, or Ph.D. in Computer Science or a related technical field (or equivalent experience).
- 8+ years of relevant work experience.
- Strong command of Python and experience building complex, well-tested software systems.
- Hands-on experience with deep learning frameworks like PyTorch or JAX; understand how models are built and where performance challenges lie.
- Solid foundation in compiler concepts such as abstract syntax trees (ASTs), intermediate representations (e.g., SSA form), program analysis, and code generation.
- Excellent communication and collaboration skills for working effectively in a distributed, open-source environment.
Benefits
NVIDIA offers highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility.