NVIDIA

1 week ago

Developer Technology Engineer - AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Build and optimize GPU-accelerated parallel algorithms for training and inference of large language models. Work with application developers and NVIDIA teams to improve architectures, software platforms, and programming models, turning real-world feedback into platform enhancements. Deeply optimize high-performance operators (GPU kernels, instruction tuning, compiler optimization) and advance distributed training/inference communication by improving communication libraries and data-transfer strategies for compute/communication overlap.

Location: Shanghai, Shenzhen, Beijing

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Partner with key application developers to understand current and future problems and deliver GPU-optimized solutions via library development and application contributions.
•Collaborate with architecture, research, libraries, tools, and system software teams to influence next-generation architectures, software platforms, and programming models.
•Optimize high-performance operators including GPU kernel optimization, instruction-level tuning, and compiler optimization across NVIDIA libraries and open-source projects.
•Advance distributed training and inference by refining communication libraries and open-source communication libraries.
•Study interconnect topologies and network protocols to design efficient data transfer strategies for compute-communication overlap.

Key Requirements

•A degree or equivalent experience in an engineering or computer science field; a masters or doctoral degree is preferred.
•2+ years of work experience.
•Solid understanding of C, C++, Python, or Fortran.
•Strong mathematical fundamentals including linear algebra and numerical methods.
•Background in parallel programming and accelerated computing, including performance analysis/tuning; GPU programming is desirable, plus distributed communication optimization experience is advantageous.

Experience:2+ yearsLarge language modelsHigh-performance computingDistributed trainingAccelerated computingOpen-source

Education:Bachelor's

Skills:CommunicationCooperationCollaborationProblem-solvingSystem architecture thinking

Tech Stack:CC++PythonFortranGPUsCUDAMegatronTRTLLMSGLangVLLMCuDNNCuBLASCUTLASSDeepGEMMFlashMLAFlashAttentionFlashinferNCCLGINNVSHMEM

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: 4.3

Website LinkedIn Glassdoor

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NVIDIA

1 week ago

Developer Technology Engineer - AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Shanghai, Shenzhen, Beijing

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Partner with key application developers to understand current and future problems and deliver GPU-optimized solutions via library development and application contributions.
•Collaborate with architecture, research, libraries, tools, and system software teams to influence next-generation architectures, software platforms, and programming models.
•Optimize high-performance operators including GPU kernel optimization, instruction-level tuning, and compiler optimization across NVIDIA libraries and open-source projects.
•Advance distributed training and inference by refining communication libraries and open-source communication libraries.
•Study interconnect topologies and network protocols to design efficient data transfer strategies for compute-communication overlap.

Key Requirements

•A degree or equivalent experience in an engineering or computer science field; a masters or doctoral degree is preferred.
•2+ years of work experience.
•Solid understanding of C, C++, Python, or Fortran.
•Strong mathematical fundamentals including linear algebra and numerical methods.
•Background in parallel programming and accelerated computing, including performance analysis/tuning; GPU programming is desirable, plus distributed communication optimization experience is advantageous.

Experience:2+ yearsLarge language modelsHigh-performance computingDistributed trainingAccelerated computingOpen-source

Education:Bachelor's

Skills:CommunicationCooperationCollaborationProblem-solvingSystem architecture thinking

Tech Stack:CC++PythonFortranGPUsCUDAMegatronTRTLLMSGLangVLLMCuDNNCuBLASCUTLASSDeepGEMMFlashMLAFlashAttentionFlashinferNCCLGINNVSHMEM

Company Brief

NVIDIA

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: 4.3

Website LinkedIn Glassdoor