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
API
Algorithms @ 3
CUDA @ 3
Debugging @ 3
Deep Learning @ 3
GPU @ 3
GenAI
Generative AI
LLM
LLVM @ 3
OpenCL @ 3
Performance Analysis @ 5
Performance Optimization
- 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
NVIDIA is hiring software engineers for the CUDA Tile team. NVIDIA GPUs enable breakthroughs in generative AI, large language models, recommendation systems, speech recognition, image classification, and other areas of deep learning.
Responsibilities
- Work on CUDA Tile, a tile-based programming model for NVIDIA GPUs that shipped with CUDA 13.1.
- Design and implement compiler transformations.
- Develop MLIR-based dialects and lowering passes.
- Optimize the performance of tile-based kernels across multiple generations of NVIDIA GPU architectures.
- Define public APIs and implement compiler and optimization techniques.
- Perform performance optimization and general software engineering work.
- Define project goals and scope and lead independent development efforts.
Requirements
- Bachelor's, master's, or Ph.D. degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
- 3+ years of relevant work or research experience in compiler optimization, performance analysis, and IR design.
- Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.
- Ability to work independently and lead development efforts.
- Strong interpersonal skills and the ability to work in a dynamic, product-oriented team.
Preferred Qualifications
- Knowledge of CPU and/or GPU architecture.
- CUDA or OpenCL programming experience.
- Experience with MLIR, LLVM, XLA, TVM, and deep learning models and algorithms.
Benefits
- Base salary range of USD 152,000–241,500 per year, determined by location, experience, and compensation for similar positions.
- Eligible for equity and benefits.
- Applications accepted at least until August 23, 2026.
- NVIDIA is an equal opportunity employer committed to an inclusive work environment.
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