Senior Deep Learning Compiler Engineer - XLA

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 versatile software engineers for our Deep Learning Compiler team. NVIDIA is at the center for the AI revolution that's transforming how people live, work, and interact with technology. Come join us to build high-performance, production-grade software that's at the core of next-generation AI systems.

What you'll be doing

In this role, develop compiler optimization algorithms for deep learning workloads. You will optimize inference and training performance for the JAX framework and the OpenXLA compiler on NVIDIA GPUs at scale. You’ll collaborate with our partners in deep learning framework teams and our hardware architecture teams to accelerate the next generation of deep learning software. The scope of these efforts include:

• Crafting and implementing compiler optimization techniques for deep learning network graphs.

• Designing novel graph partitioning and tensor sharding techniques for distributed training and inference.

• Performance tuning and analysis.

• Code-generation for NVIDIA GPU backends using open-source compilers such as MLIR, LLVM and OpenAI Triton.

• Designing user facing features in JAX and related libraries and other general software engineering work.

• Working closely with GPU hardware engineering teams to design AI compiler software features for next-generation GPUs.

What we need to see

• Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field (or equivalent experience).

• 4+ years of relevant work or research experience in performance analysis and compiler optimizations.

• Ability to work independently, define project goals and scope, and lead your own development effort adopting clean software engineering and testing practices.

• Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.

• Strong foundation in architecture of CPU, GPUs or other high performance hardware accelerators. Knowledge of high-performance computing and distributed programming.

• CUDA or OpenCL programming experience is desired but not required.

• Experience with the following technologies is a huge plus: XLA, TVM, MLIR, LLVM, OpenAI Triton, deep learning models and algorithms, and deep learning framework design.

• Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team. A history of mentoring junior engineers and interns is a bonus.

Ways to stand out from the crowd

• Experience working deep learning frameworks such as JAX, PyTorch or TensorFlow.

• Extensive experience with CUDA or with GPUs in general.

• Experience with open-source compilers such as XLA, LLVM, MLIR or TVM.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 235,750 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.Applications for this job will be accepted at least until July 29, 2025.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.

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