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4 дня назад

Algorithm Engineer (AI)

Формат работы
onsite
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
Taiwan
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Algorithm Engineer (AI/Computer Vision): Developing next-generation optical inspection and metrology solutions for the semiconductor industry with an accent on image processing, signal processing, and AI algorithms. Focus on designing high-performance algorithms, implementing them in C++/Python, and optimizing them for production deployment in semiconductor fabs.

Location: Hsinchu, Taiwan (onsite support at TSMC required)

Company

Global leader in diversified electronics for the semiconductor manufacturing ecosystem, investing 15% of sales back into R&D.

What you will do

  • Design and optimize algorithms for semiconductor inspection and metrology systems.
  • Manage the full algorithm lifecycle: modeling, simulation, implementation, and validation.
  • Collaborate with cross-functional teams to prototype and deploy new capabilities.
  • Troubleshoot and resolve complex production issues onsite at customer fabs, including TSMC.
  • Analyze large-scale production data to improve algorithm robustness and defect detection performance.

Requirements

  • Degree in a relevant field: PhD (0 years), Master's (3+ years), or Bachelor's (5+ years) experience.
  • Proficiency in C/C++, MATLAB, and/or Python.
  • Strong foundation in image processing, signal processing, machine learning, or computer vision.
  • Must be based in or able to work onsite in Hsinchu, Taiwan.
  • Ability to collaborate with globally distributed, multidisciplinary teams.

Nice to have

  • Experience with CPU optimization (SIMD, SSE, AVX).
  • GPU programming skills using CUDA.
  • Knowledge of high-performance computing and algorithm acceleration.

Culture & Benefits

  • Competitive and family-friendly total rewards package.
  • Inclusive work environment with diverse benefit programs.
  • Opportunity to tackle high-complexity problems in a highly innovative R&D culture.

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