Developer Technology Engineering Intern - 2027

NVIDIA
Beijing, Shanghai
InternshipFunction: Software EngineeringSkills: ["Communication","Collaboration","Cooperation","Problem-solving"]

Join NVIDIA’s Compute Developer Technology (DevTech) team to work with application developers on GPU-accelerated parallel algorithms, data structures, and performance optimization. You’ll contribute to large language model (LLM) training and inference improvements, including operator and compiler/kernel tuning, and help advance distributed communication efficiency using NVIDIA and open-source libraries. Collaborate with architecture, research, and systems teams from concept through production.

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FursaFursa
NVIDIA
NVIDIA
1 day ago

Developer Technology Engineering Intern - 2027

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Last checked: 6 hours agoStatus: Live

Job Summary

Join NVIDIA’s Compute Developer Technology (DevTech) team to work with application developers on GPU-accelerated parallel algorithms, data structures, and performance optimization. You’ll contribute to large language model (LLM) training and inference improvements, including operator and compiler/kernel tuning, and help advance distributed communication efficiency using NVIDIA and open-source libraries. Collaborate with architecture, research, and systems teams from concept through production.
Location: Beijing, Shanghai
Employment Type: Internship
Job Function: Software Engineering
Seniority: Intern level

Key Responsibilities

  • •Work with application developers to understand current and future problems and build/optimize parallel algorithms and data structures for GPU-accelerated solutions.
  • •Contribute to training and inference optimization for large language models, including library development and direct application contributions within LLM ecosystems.
  • •Collaborate with architecture, research, libraries, tools, and system software teams to influence next-generation architectures, software platforms, and programming models.
  • •Optimize high-performance operators through GPU kernel optimization, instruction-level tuning, and compiler optimization to improve application performance and developer efficiency.
  • •Advance distributed training and inference communication by refining communication libraries and designing efficient data transfer strategies to enable compute-communication overlap.

Key Requirements

  • •An engineering or computer science degree (or equivalent experience) from a university; a master’s or doctoral candidate is preferred.
  • •Strong foundation in C, C++, Python, or Fortran.
  • •Strong understanding of software development, programming techniques, algorithms, and mathematical fundamentals (e.g., linear algebra and numerical methods).
  • •Background in parallel programming and accelerated computing, including experience with performance analysis and tuning; GPU programming is desirable.
  • •Experience optimizing large language models and/or high-performance computing, with familiarity across operator-, framework-, and algorithm-level optimization; distributed communication optimization is highly advantageous.
Experience:Large language modelsHigh-performance computingDistributed trainingOpen source
Skills:CommunicationCollaborationCooperationProblem-solving
Tech Stack:CC++PythonFortranGPUMegatronTRTLLMSGLangVLLMCuDNNCuBLASCUTLASSDeepGEMMFlashMLAFlashAttentionFlashinferNCCLNCCL GINNVSHMEMDeepEP

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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