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# Senior Deep Learning Compiler Engineer - PyTorch

- **Company:** Nvidia
- **Location:** Berlin, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Code Generation, Nvidia CUDA, Distributed Systems, Python (Programming Language), Open Source Technology, Program Analysis, Software Systems, Pytorch, Deep Learning, Parallel Computation, Information Technology
- **Published:** September 25, 2026
- **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Germany-Berlin/Senior-Deep-Learning-Compiler-Engineer---PyTorch_JR2001403

## About the Role

We are looking for engineers who are excited about building powerful, user-centric tools and are comfortable working in a fast-paced, collaborative environment. Here are some of the expertise we would like to see:

 * A Bachelor's, Master's, or Ph.D. in Computer Science or a related technical field (or equivalent experience).
 * 8+ years of relevant work experience
 * A strong command of Python and experience building complex, well-tested software systems.
 * Hands-on experience with deep learning frameworks like PyTorch or JAX. You understand how models are built and where the performance challenges lie.
 * A 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, essential for working effectively in a distributed, open-source environment.

Ways to stand out from the crowd:

 * Previous contributions to deep learning compiler projects (e.g., TVM, MLIR, IREE) or deep learning frameworks themselves.
 * Deep expertise in the internals of PyTorch, particularly its compiler stack (TorchDynamo, TorchInductor).
 * Experience with JAX-like functional transformations and their application in a compiler context.
 * Familiarity with parallel programming, distributed systems, and writing high-performance CUDA code.
 * A track record of impactful participation in open-source communities, such as through code contributions, design discussions, or mentorship.



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