Deep Learning Performance Architect

at Nvidia

📍 Santa Clara, United States

$148,000-276,000 per year

SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Python @ 4 Algorithms @ 4 Distributed Systems @ 4 TensorFlow @ 4 Parallel Programming @ 4 PyTorch @ 4

Details

NVIDIA is seeking outstanding Performance Analysis Architects to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications.

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run AI algorithms, simulating human intelligence, and act as the brains of computers, robots and self-driving cars that can perceive and understand the world. Increasingly known as “the AI computing company”, NVIDIA wants you. Come, join our Deep Learning Architecture team, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly growing field!

Responsibilities

  • Develop innovative architectures to extend the state of the art in deep learning performance and efficiency.
  • Prototype key deep learning and data analytics algorithms and applications.
  • Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites.
  • Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications.
  • Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW.

Requirements

  • MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent experience.
  • 3+ years of relevant work experience.
  • Strong background in computer architecture and deep learning.
  • Expert programming skills in Python, C, C++.
  • Experience with performance and power modeling, architecture simulation, profiling, and analysis.

Ways to stand out from the crowd

  • Background in large scale distributed systems architectures and/or a background with GPU Computing and parallel programming models such as CUDA.
  • Experience with deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, Tensorflow, TensorRT).
  • Experience with the architecture of or workload analysis on other DL accelerators.

The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. You will also be eligible for equity and benefits.