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Thinh Nguyen Quang

Thinh Nguyen Quang

AI engineer

Nhân tài
Ho Chi Minh CityThành viên từ 14 tháng 4, 2026
PythonCDiffusion modelsStyle transferDifferentiable renderingVector graphicsLatent injectionAttention swappingSupervised learningUnsupervised learningCNNRNNTransformersLLM fine-tuningRAGSemantic searchRerankingPrompt engineeringNumPyPandasMatplotlibSeabornEDAPyTorchHuggingFaceFAISSOpenCVGitLinuxProblem solvingTeam collaborationAdaptabilityCritical thinking
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Thuê người này

Gửi đề nghị công việc trực tiếp cho ứng viên này

PythonCDiffusion modelsStyle transferDifferentiable rendering

Giới thiệu

Senior IT student at Vietnam National University Ho Chi Minh City, University of Science (VNU-HCM HCMUS), with hands-on experience from an internship at Bosch developing AI-powered image detection systems and automated training pipelines. Passionate about building end-to-end vision systems spanning diffusion models, style transfer, and differentiable vector rendering. Looking to contribute to production AI teams and grow as a Computer Vision Engineer.

Kinh nghiệm

AI Engineer Intern at Bosch Global Software Technologies Company Limited (2025-05 – 2025-11)

Developed AI-powered image detection systems and automated training pipelines

  • Developed few-shot learning module (IconSpotter) for UI icon detection and classification using SAM2 (detection) and DINOv3 (feature extraction), achieving high accuracy from a single reference image
  • Built automated training pipelines (SwiftBoard) for rapid model adaptation, integrating data collection, quality validation, pre-labeling, and DANN-based domain adaptation, improving accuracy from 66% to 98% and reducing the adaptation cycle for each new board from weeks to hours
  • Collaborated closely with test engineers to validate AI model performance, and real-time response efficiency
  • Maintained scalable micro-AI services with improved efficiency

Học vấn

Honors Bachelor of Information Technology Program in Information Technology – University of Science, VNU-HCM (2022 – 2026)

Kỹ năng

AI engineer

Đánh giá

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