Developer Technology Engineer - AI
@ NVIDIA

Beijing, Beijing, China
$150,000
On Site
Full Time
Posted 16 hours ago

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Job Details

Overview

NVIDIA is looking for a passionate, world-class computer scientist to join its Compute Developer Technology (DevTech) team. As a Developer Technology Engineer - AI, you will research and develop techniques to GPU-accelerate leading applications in high performance computing fields including machine and deep learning, scientific computing, and data processing.

What You Will Be Doing

You will work directly with key application developers, particularly those focused on large language models (LLM), to understand current and future challenges. Responsibilities include creating and optimizing core parallel algorithms and data structures through library development and direct contributions to applications.

Your role involves:

  • Optimizing training and inference for large language models.
  • Contributing to frameworks such as Megatron, TRTLLM, SGLang, and vLLM.
  • Collaborating with architecture, research, libraries, tools, and system software teams on next-generation GPU architectures and platforms.
  • Engaging in deep optimization projects including CUDA deep optimization and compiler enhancements.
  • Occasional travel for conferences and on-site developer visits.

What We Need To See

Requirements for this role include:

  • A degree in engineering or computer science (BS; MS or PhD preferred).
  • 2+ years of relevant work experience.
  • Strong knowledge of C/C++ and/or Fortran.
  • Deep understanding of software design, programming techniques, and algorithms.
  • Expertise in LLM training/inference optimization, distributed training/inference and related technologies such as NCCL, NVSHMEM, IB, RoCE.
  • Solid mathematical fundamentals, including linear algebra and numerical methods.
  • Experience with parallel programming, especially with CUDA C/C++ and OpenACC.
  • Good communication, organization, and problem-solving skills.

Key Skills/Competency

  • GPU Acceleration
  • Parallel Programming
  • LLM Optimization
  • C/C++
  • CUDA
  • High Performance Computing
  • Software Optimization
  • Distributed Training
  • Mathematics
  • Algorithm Development
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How to Get Hired at NVIDIA

🎯 Tips for Getting Hired

  • Customize your resume: Highlight GPU and parallel programming skills.
  • Leverage networking: Connect with NVIDIA employees on LinkedIn.
  • Research NVIDIA: Understand their projects and cutting-edge tech.
  • Prepare for technical interviews: Review CUDA and optimization cases.

📝 Interview Preparation Advice

Technical Preparation

Review CUDA optimization cases.
Practice parallel programming challenges.
Study GPU architecture fundamentals.
Refine C/C++ coding proficiency.

Behavioral Questions

Describe a project managing technical challenges.
Explain a time you solved a difficult problem.
Share examples of teamwork under tight deadlines.
Discuss handling complex project priorities.

Frequently Asked Questions