Senior Deep Learning Compiler Engineer - CUDA
NVIDIA - Washington
Work at NVIDIA
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Overview
Senior Deep Learning Compiler Engineer - CUDA
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Senior Deep Learning Compiler Engineer - CUDA
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NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are looking for outstanding ML/DL compiler engineers to join the team and develop groundbreaking technologies in machine learning compilers and AI systems. We are building foundation compiler technology for the next generation of CUDA programming model that accelerates AI application with rapidly evolving GPU architectures. As a member of the team, you will develop technologies that have a big impact on millions of CUDA developers, all AI frameworks, and even application areas that are beyond AI. You will develop new ML/DL compiler abstractions, build runtimes, and ML/DL -compiler driven system solutions to accelerate large language models, agents and other high-impact machine learning workloads. As part of this role, you will be building a close technical relationship with internal NVIDIA software and hardware teams on push the latest developments to NVIDIA's product.
What You'll Be Doing
- Design and implement Pythonic language interface for tile-aware GPU programming
- Optimizing compiler pipelines for efficient execution
- Integrate with AI/ML frameworks
- Develop performance critical primitives for tensor operations and memory operations
- Collaborate with hardware teams to co-design compiler optimizations for emerging GPU architectures, including Tensor Core utilization and distributed execution
- Bachelor's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD are preferred
- 5+ years (academic/ industry) experience with ML/DL systems development preferable for compilers
- Strong Python and C/C++ programming skills
- Expert experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, Triton, etc.)
- Strong sense of ownership, fast learner, passion for quality and user experience
- Proficiency in Python and C++ for DSL development and low-level compiler internals
- Experience with compiler frameworks (Triton, LLVM, MLIR,TVM) and IR design for GPUs
- Deep understanding of GPU architectures (CUDA cores, Tensor Cores, memory hierarchies) and tile-based execution models
- Strong experience machine learning systems research and productionization
- Open source project ownership or contributions
The base salary range is 148,000 USD - 287,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
You will also be eligible for equity and benefits . NVIDIA accepts applications on an ongoing basis.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
JR1999064
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Full-time
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Industries
Computer Hardware Manufacturing, Software Development, and Computers and Electronics Manufacturing
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