Developer Technology Engineer AI
@ NVIDIA

Beijing, Beijing, China
$150,000
On Site
Full Time
Posted 19 hours ago

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Job Details

About NVIDIA

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 30 years. Today, the company is tapping into the unlimited potential of AI to define the next era of computing, where GPUs empower computers, robots, and self-driving cars.

What You'll Be Doing

As a Developer Technology Engineer AI, you will work directly with key application developers to:

  • Understand current and future challenges.
  • Craft and optimize core parallel algorithms and data structures using GPUs.
  • Develop reference code and contribute directly to applications.
  • Collaborate with architecture, research, libraries, tools, and system software teams.
  • Travel for conferences and on-site developer visits occasionally.

What We Need To See

The ideal candidate will have:

  • A BS, MS, or PhD in engineering or computer science (or equivalent experience).
  • 3+ years of experience and programming proficiency in C/C++ and/or Python.
  • 2+ years of experience with LLM training framework development and performance optimization.
  • Strong mathematical fundamentals (linear algebra and numerical methods).
  • Expertise in parallel programming, ideally with CUDA C/C++.
  • Excellent communication, organization, and problem-solving skills.

Key Skills/Competency

  • GPU
  • AI
  • C/C++
  • Python
  • CUDA
  • Parallel Programming
  • LLM
  • Algorithms
  • Data Structures
  • Numerical Methods

About the Role

This role is a chance to join a diverse and innovative team that influences next-generation architectures and software platforms.

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How to Get Hired at NVIDIA

🎯 Tips for Getting Hired

  • Customize Your Resume: Highlight GPU, CUDA, and AI expertise.
  • Tailor Application: Emphasize C/C++ and Python proficiency.
  • Research NVIDIA: Understand their tech evolution and innovation.
  • Prepare for Interviews: Practice algorithm, design, and parallel programming questions.

📝 Interview Preparation Advice

Technical Preparation

Review GPU and CUDA documentation.
Practice C/C++ algorithm challenges.
Study parallel programming techniques.
Refresh mathematical fundamentals.

Behavioral Questions

Demonstrate teamwork in cross-functional projects.
Showcase problem-solving scenarios from past.
Explain time management with examples.
Discuss communication in technical challenges.

Frequently Asked Questions