המקום בו המומחים והחברות הטובות ביותר נפגשים
What you will be doing:
Understand, analyze, profile, and optimize AI and deep learning training workloads on state-of-the-art hardware and software platforms.
Understand the big picture of training performance on GPUs, prioritizing and then solving problems across many dozens of state-of-the-art neural networks.
Implement production-quality software in multiple layers of NVIDIA's deep learning platform stack, from drivers to DL frameworks.
Implement key DL training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
Build tools to automate workload analysis, workload optimization, and other critical workflows.
What we want to see:
PhD (or equivalent experience) in CS, EE or CSEE and 5+ years; or MS and 8+ years of relevant work experience.
Strong background in deep learning and neural networks, in particular training.
Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture.
Proven experience analyzing and tuning application performance.
Experience with processor and system-level performance modelling.
Programming skills in C++, Python, and CUDA.
משרות נוספות שיכולות לעניין אותך