Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Python @ 4
Algorithms @ 4
Hiring @ 4
Debugging @ 4
API @ 4
LLM @ 4
PyTorch @ 4
CUDA @ 6
GPU @ 4
Deep Learning @ 7
AI @ 7
Robotics @ 4
OpenCL @ 6
Performance Analysis @ 4
- 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's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”.
We are hiring software engineers for the Deep Learning & AI Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas (large language models, generative AIs, recommendation systems, image classification, speech recognition, etc.). Our DLC is the backbone of NVIDIA’s inference engine across data centers, personal devices, automotive, and robotics, delivering inference performance, fast build time, reduced memory footprints, and ease of use for both Ahead-of-Time and Just-in-Time compilation.
Applications for this job will be accepted at least until February 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer.
Responsibilities
- Develop compiler IR, programming model, and optimizations for future GPU architectures.
- Collaborate with deep learning software framework teams and hardware architecture teams to accelerate next-generation deep learning software.
- Define public APIs, perform performance optimizations and analysis, craft and implement compiler optimizations and kernel generation for neural networks.
- General software engineering tasks including debugging, performance tuning, and test design.
Requirements
- Bachelors, Masters, or Ph.D. in Computer Science, Computer Engineering, related field, or equivalent experience.
- 3+ years of relevant work or research experience in performance analysis and compiler optimizations.
- Experience with compiler technologies (e.g., MLIR, XLA, LLVM).
- Excellent C++ and Python programming and software design skills, including debugging, performance analysis, and test design.
- Ability to work independently, define project goals and scope, and lead your own development efforts.
- Strong interpersonal skills and ability to work in a fast-moving, dynamic product-oriented team.
Ways to stand out
- Understanding of deep learning models, algorithms and frameworks, such as PyTorch and XLA.
- Understanding of LLM inference optimizations and techniques.
- GPU kernel generation with high performance and fast build time.
- Proficiency in GPU architecture; CUDA or OpenCL programming experience.
- Track record on new hardware bring-up is a plus.
Compensation & Benefits
- Base salary range: 152,000 USD - 241,500 USD (your base salary will be determined based on your location, experience, and pay of employees in similar positions).
- Eligible for equity and benefits. (Link to benefits provided in original posting.)