Senior Deep Learning Compiler Engineer - XLA

About the role

NVIDIA is seeking versatile software engineers for its XLA team. The position involves developing compiler optimization algorithms for deep learning workloads, optimizing inference and training performance for the JAX framework and the OpenXLA compiler on NVIDIA GPUs at scale. Collaboration with deep learning framework teams and hardware architecture teams is essential.

Responsibilities

• 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 like MLIR, LLVM, and OpenAI Triton.
• Designing user-facing features in JAX and related libraries, and performing general software engineering tasks.
• Collaborating with GPU hardware engineering teams to design AI compiler software features for next-generation GPUs.

Requirements

• Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, or 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 while 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.

Preferred Qualifications

• Experience working with 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.

What We Offer

• Competitive salaries and a generous benefits package.
• Opportunities for equity and benefits.

How to Apply

Applications for this job will be accepted at least until March 1, 2026. This posting is for an existing vacancy.