11 hours ago

Developer Technology Intern, AI

NVIDIA

On Site
Full Time
$100,000
Santa Clara, CA

Job Overview

Job TitleDeveloper Technology Intern, AI
Job TypeFull Time
Offered Salary$100,000
LocationSanta Clara, CA

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Job Description

About NVIDIA

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!

The Developer Technology Team

The Developer Technology team at NVIDIA plays a pivotal role in extracting maximum performance from our computing platform, which enables researchers to develop and productize state-of-the-art technologies. Do you share our passion for Artificial Intelligence? Come join a team full of outstanding engineers to work on the AI Developer Technology team.

What You Will Be Doing as a Developer Technology Intern, AI

  • Study and develop state-of-the-art techniques in deep learning and machine learning and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures.
  • Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models.

What We Need To See

  • Pursuing an MS or PhD in an engineering or Computer Science related discipline or equivalent program area.
  • You'll possess strong knowledge of C/C++, software development, programming techniques, and AI algorithms.
  • Experience with parallel programming and performance optimizations, ideally CUDA.
  • Mathematical fundamentals, including linear algebra.
  • Experience with Deep Learning models through frameworks like PyTorch, JAX, DGL, PyG.
  • Excellent communication and organization skills, with a logical approach to problem solving, time management, and task prioritization skills.
  • Experience with low-precision arithmetic.

Way To Stand Out From The Crowd

  • Experience with CUTLASS, optimizing linear algebra on GPUs, and multi-GPU programming.
  • Knowledge of high-performance computing (HPC), including GPU and CPU architecture, networking, and HPC software.
  • Experience profiling and optimizing CUDA kernels.
  • Knowledge of programming and debugging software systems at scale using common HPC libraries like MPI.

Why Join NVIDIA?

NVIDIA is widely considered to be one of the technology world’s most desirable employers with some of the most forward-thinking, inventive, and hardworking people working here - we need your help to build our future. Are you creative, ambitious, and love challenges? We want to hear from you!

Key skills/competency

  • Deep Learning
  • Machine Learning
  • GPU Optimization
  • CUDA
  • C/C++
  • Parallel Programming
  • AI Algorithms
  • PyTorch
  • Linear Algebra
  • High-Performance Computing (HPC)

Tags:

AI Developer Intern
Deep Learning
Machine Learning
GPU Optimization
Parallel Programming
AI Algorithms
Software Development
Performance Analysis
Research
Collaboration
System Architecture
C++
CUDA
PyTorch
JAX
CUTLASS
MPI
HPC
Linear Algebra
Low-Precision Arithmetic
Debugging

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How to Get Hired at NVIDIA

  • Research NVIDIA's AI vision: Study their commitment to AI, GPU innovation, and impact on various industries like robotics and autonomous vehicles. Understand their culture of "inventive and hardworking people."
  • Showcase GPU optimization expertise: Tailor your resume to highlight experience with CUDA, parallel programming, and performance optimization of AI algorithms on GPUs. Quantify achievements where possible.
  • Master deep learning frameworks: Demonstrate strong proficiency in PyTorch, JAX, DGL, or PyG. Be ready to discuss specific projects or contributions involving these frameworks.
  • Prepare for technical depth: Expect in-depth questions on C/C++, linear algebra, AI algorithms, and potentially HPC concepts. Practice problem-solving related to GPU performance.
  • Highlight collaboration and problem-solving: Emphasize your communication, organization, and logical problem-solving skills, crucial for cross-functional teamwork within NVIDIA's Developer Technology team.

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