Deep Learning Software Engineering Intern, Test Development - 2027

NVIDIA
Shanghai
Workplace: OnsiteInternshipFunction: Data Science & Machine LearningEducation: mastersSkills: ["Communication","Responsiveness","Thoroughness","Teamwork","Efficiency improvement"]

Join NVIDIA’s Deep Learning Software Quality Assurance team to build and automate GPU software tests that validate robustness and performance for deep learning frameworks. You’ll implement functionality, compatibility, and performance testing across the DL software stack, triage issues with development teams, and improve complex test plans. Use AI-powered tooling to generate test artifacts, detect defects, and streamline workflows while supporting release-critical development for large-scale AI products.

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FursaFursa
NVIDIA
NVIDIA
1 day ago

Deep Learning Software Engineering Intern, Test Development - 2027

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Source: Company careers pageValidated by: Fursa AI
Last checked: 10 hours agoStatus: Live
Reposted: similar role first listed 3 days ago

Job Summary

Join NVIDIA’s Deep Learning Software Quality Assurance team to build and automate GPU software tests that validate robustness and performance for deep learning frameworks. You’ll implement functionality, compatibility, and performance testing across the DL software stack, triage issues with development teams, and improve complex test plans. Use AI-powered tooling to generate test artifacts, detect defects, and streamline workflows while supporting release-critical development for large-scale AI products.
Location: Shanghai
Workplace: Onsite
Employment Type: Internship
Job Function: Data Science & Machine Learning
Seniority: Intern level

Key Responsibilities

  • •Improve GPU software testing and test automation for NVIDIA deep learning products such as cuDNN and TensorRT.
  • •Own functionality, compatibility, and performance testing for releases across the deep learning software stack.
  • •Collaborate with development teams to triage issues, perform root-cause analysis, verify fixes, and define new tests.
  • •Utilize AI-powered tools to generate test cases/plans/scripts and assist with defect detection and bug fixing.
  • •Continuously improve test plans and workflow processes to increase efficiency and quality across DL SW QA.

Key Requirements

  • •Pursuing an MS or higher degree in CS/EE/CE.
  • •Proficiency in scripting languages including Python, Perl, and bash, with Linux knowledge required.
  • •Experience with C/C++ programming is a plus.
  • •Familiarity with deep learning frameworks is a strong plus.
  • •Good communication skills with fluent oral and written English, plus experience with AI tools.
Experience:Deep learningGPU computing
Education:Master's in CS/EE/CE
Skills:CommunicationResponsivenessThoroughnessTeamworkEfficiency improvement
Languages:English
Tech Stack:CuDNNTensorRTTensorFlowPyTorchMxNETPythonPerlBashLinuxCC++CUDAGPU computingAI tools

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
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Glassdoor: 4.3
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