Senior ML Compiler Engineer

NVIDIA•Redmond, WA

10h

About The Position

NVIDIA's invention of the GPU 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 looking for outstanding ML/DL compiler engineers to join the team and develop groundbreaking technologies in machine learning compilers and AI systems. We build innovative AI compiler solutions that work together with NVIDIA's software stack to provide comprehensive acceleration for modern machine learning models. As a member of the team, you will develop innovative AI compiler technologies for NVIDIA's hardware architecture. You will develop new ML/DL compiler abstractions, build efficient attention 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 to push the latest developments to NVIDIA's product.

Requirements

Bachelor's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD are preferred
4+ years (academic/ industry) experience in machine learning systems development – including ML compilers, LLM inference kernels, kernel generations.
Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX etc)
Strong python and C/C++ programming skills

Nice To Haves

Expertise in AI frameworks such as PyTorch, TensorFlow, and ONNX
Expertise in machine learning compilers (e.g. Apache TVM, MLIR)
Expertise in domain specific compiler and library solutions for LLM inference and training (e.g. FlashInfer, Flash Attention)
Strong experience in GPU performance optimizations as well as experience machine learning systems research and productization
Open source project ownership or contributions

Responsibilities

Innovate and develop new machine learning compiler and systems technologies
Design, implement, and optimize compilers for high impact AI workloads
Building strong kernel and domain specific language solutions for state of art kernels in LLM inference workloads
Developing AI-driven solutions to automate the overall development flow.
Co-design learning system solutions with current and future ML compiler and algorithm technologies.
Collaborate closely with other engineering teams at NVIDIA to build high impact solutions for machine learning acceleration