Senior Deep Learning Compiler Engineer - CUDA- Seattle-Nvidia Graphics Pvt Ltd-5

Senior Deep Learning Compiler Engineer - CUDA NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Its a unique legacy of innovation thats fueled by great technology and amazing people. Today, were tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. 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 are building foundation compiler technology for the next generation of CUDA programming model that accelerates AI applications with rapidly evolving GPU architectures. As a member of the team, you will develop technologies that have a big impact on millions of CUDA developers, all AI frameworks, and even application areas that are beyond AI. What you'll be doing: Design and implement Pythonic language interface for tile-aware GPU programming Optimizing compiler pipelines for efficient execution Integrate with AI/ML frameworks Develop performance critical primitives for tensor operations and memory operations Collaborate with hardware teams to co-design compiler optimizations for emerging GPU architectures, including Tensor Core utilization and distributed execution What we need to see: Bachelor's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD are preferred 5 years (academic/industry) experience with ML/DL systems development preferable for compilers Strong Python and C/C programming skills Expert experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, Triton, etc.) Strong sense of ownership, fast learner, passion for quality and user experience Ways To Stand Out From The Crowd: Proficiency in Python and C for DSL development and low-level compiler internals Experience with compiler frameworks (Triton, LLVM, MLIR, TVM) and IR design for GPUs Deep understanding of GPU architectures (CUDA cores, Tensor Cores, memory hierarchies) and tile-based execution models Strong experience in machine learning systems research and productionization Open source project ownership or contributions NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Locations - US, WA, Seattle #J-18808-Ljbffr