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12 часов назад

Deep Learning Software Engineer (AI)

Формат работы
onsite
Тип работы
fulltime
Грейд
junior
Английский
b2
Страна
China
Вакансия из списка Hirify.GlobalВакансия из Hirify RU Global, списка компаний с восточно-европейскими корнями
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Описание вакансии

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TL;DR

Deep Learning Software Engineer (AI): Designing and optimizing AI software frameworks and machine learning primitives with an accent on distributed algorithm implementation and computational graph transformation. Focus on profiling deep learning models to resolve performance bottlenecks and developing efficient code for diverse hardware backends.

Location: On-site in Shanghai, China

Company

hirify.global is a global leader in computing technology, driving innovation in hardware and software solutions to shape the future of technology.

What you will do

  • Design, develop, and optimize AI frameworks and machine learning libraries.
  • Implement distributed algorithms including data parallel frameworks and asynchronous communication.
  • Transform neural network computational graph representations.
  • Profile deep learning models to identify and resolve performance bottlenecks.
  • Develop machine learning primitives within mathematical libraries.
  • Collaborate with researchers to optimize code for various computing hardware backends.

Requirements

  • Master degree or Ph.D. in Computer Science, Artificial hirify.globalligence, or a related field.
  • Proficiency in modern C++ and Python programming.
  • Foundational knowledge of Deep Learning theory and practical hands-on experience.
  • Fluent in written and spoken English.
  • Must be based in Shanghai for on-site work.

Nice to have

  • Experience with performance optimization or high-efficiency kernel development.
  • Knowledge of PyTorch, SGLang, or vLLM.
  • Deep understanding of LLM model structures.

Culture & Benefits

  • Opportunities for career advancement and skill development within a global corporation.
  • Exposure to cutting-edge AI research and hardware-level optimization.
  • Collaboration with diverse, high-impact engineering and research teams.
  • Commitment to ethical hiring practices and professional growth.

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