Deep Learning Compiler Engineer

🔥 0 minutes ago

🏄 California, Oregon, +2 more states – Remote

🏄 California – Remote 🌲 Oregon – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $152k - $241.5k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷🏻‍♀️ Engineer

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👻 Ghost score 1%

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Work on CUDA Tile, a tile-based programming model for NVIDIA GPUs • Design and implement compiler transformations • Develop MLIR-based dialects and lowering passes • Optimize tile-based kernel performance across multiple generations of NVIDIA GPU architectures • Define public APIs • Craft and implement compiler and optimization techniques • Perform performance optimization and general software engineering work • Collaborate with a product-oriented team

🎯 Requirements

• Bachelor's, Master's or Ph.D. in Computer Science, Computer Engineering or a related field (or equivalent experience) • 3+ years of relevant work or research experience in compiler optimization, performance analysis and IR design • Ability to work independently, define project goals and scope, and lead your own development effort • Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design • Strong interpersonal skills and ability to work in a dynamic product-oriented team • Knowledge of CPU and/or GPU architecture • CUDA or OpenCL programming experience • Experience with MLIR, LLVM, XLA, TVM and deep learning models and algorithms

🏖️ Benefits

• Equity • Comprehensive benefits package