Senior Deep Learning Compiler Engineer - CUDA

NVIDIA is seeking an exceptional Senior Deep Learning Compiler Engineer to join their CUDA team, working at the forefront of AI and accelerated computing. This role combines cutting-edge machine learning compiler development with high-performance GPU computing, offering an opportunity to impact millions of CUDA developers worldwide.

The position involves developing groundbreaking technologies in machine learning compilers and AI systems, specifically building foundation compiler technology for the next generation of CUDA programming model. You'll be working on accelerating AI applications with rapidly evolving GPU architectures, developing new ML/DL compiler abstractions, building runtimes, and creating compiler-driven system solutions to accelerate large language models and other high-impact machine learning workloads.

As a senior engineer, you'll collaborate closely with NVIDIA's software and hardware teams, pushing the boundaries of what's possible with GPU computing. The role requires expertise in both Python and C++ programming, deep understanding of compiler frameworks, and significant experience with deep learning systems. You'll be working with state-of-the-art technologies including PyTorch, JAX, Triton, and LLVM, while having the opportunity to contribute to open-source projects.

NVIDIA offers a highly competitive compensation package, including a base salary range of $148,000 - $287,500 USD, equity, and comprehensive benefits. The company is known for its innovative culture and is consistently ranked as one of the technology industry's most desirable employers. You'll be joining a diverse team working on transformative technologies in AI, digital twins, and accelerated computing, with the opportunity to make a lasting impact on the world.

The ideal candidate will bring strong technical expertise in compiler development, machine learning systems, and GPU architectures, combined with a collaborative mindset and passion for innovation. This role offers the perfect blend of theoretical computer science and practical engineering, with the opportunity to work on technologies that are shaping the future of computing.