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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”.\nNVIDIA 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.\nWhat you’ll be doing:\nDrive technical innovation: Participating in hands-on development focusing on kernel generation and computational graph optimizations for next-generation NVIDIA GPUs.\n\nAdvance 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.\n\nCollaborate on hardware/software co-design: Partner with leading experts across our software, hardware, and research divisions to architect and co-design future silicon.\n\nScale AI to the datacenter: Participating in the advancement and optimization of datacenter-scale AI workload deployments.\n\nWhat we need to see:\nBS or MS in Computer Science, Computer Engineering, or a related field (or equivalent experience). A PhD is strongly preferred.\n\nCompiler Experience: 3+ years of relevant industry experience specializing in compiler optimizations, synthesis, and placement.\n\nMLIR Knowledge: Demonstrated, hands-on experience working with MLIR.\n\nProgramming Excellence: Exceptional C/C++ and Python programming and software design skills, including rigorous debugging, performance analysis, and test design.\n\nTeam Dynamics: Strong communication and interpersonal skills, with the ability to collaborate effectively in a dynamic, fast-paced, and product-oriented environment.\n\nWays to stand out from the crowd:\nHardware Implementation: Hands-on experience implementing complex AI workloads on CPU, GPU, and/or custom AI accelerator architectures.\n\nLLM Knowledge: Deep understanding of Large Language Model (LLM) inference and its profound implications on computer architecture.\n\nArchitecture & Design: Demonstrated understanding in the designing and architecting of comprehensive compiler frameworks from the ground up.\n\nWith 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. 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