Compiler Engineer - AI Inference
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”.
NVIDIA is seeking top-tier AI Compiler Engineer to drive innovation within our world-class compiler organization. In this role, you will push the boundaries of what is possible in AI performance and help build the technology that powers the next generation of computing. Join us and make a tangible impact on a global scale.
What you’ll be doing:
Drive technical innovation: Participating in hands-on development focusing on kernel generation and computational graph optimizations for next-generation NVIDIA GPUs.
Advance the state-of-the-art: Solve complex compilation problems for AI workloads (both inference and training) and successfully transition these breakthroughs into enterprise and consumer products.
Collaborate on hardware/software co-design: Partner with leading experts across our software, hardware, and research divisions to architect and co-design future silicon.
Scale AI to the datacenter: Participating in the advancement and optimization of datacenter-scale AI workload deployments.
What we need to see:
BS or MS in Computer Science, Computer Engineering, or a related field (or equivalent experience). A PhD is strongly preferred.
Compiler Experience: 3+ years of relevant industry experience specializing in compiler optimizations, synthesis, and placement.
MLIR Knowledge: Demonstrated, hands-on experience working with MLIR.
Programming Excellence: Exceptional C/C++ and Python programming and software design skills, including rigorous debugging, performance analysis, and test design.
Team Dynamics: Strong communication and interpersonal skills, with the ability to collaborate effectively in a dynamic, fast-paced, and product-oriented environment.
Ways to stand out from the crowd:
Hardware Implementation: Hands-on experience implementing complex AI workloads on CPU, GPU, and/or custom AI accelerator architectures.
LLM Knowledge: Deep understanding of Large Language Model (LLM) inference and its profound implications on computer architecture.
Architecture & Design: Demonstrated understanding in the designing and architecting of comprehensive compiler frameworks from the ground up.
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.
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