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(Sr./Staff) Algorithm Engineer (Computer Vision)

OMNIVISION

Singapore · Tempo total

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Experiência
Qualquer
Salário
Vagas
1
Publicado
há 1 semana
Modo de trabalho
No escritório
Educação
Ph.D./M.S. in Electrical Engineering, Computer Science, Computational Imaging, Applied Mathematics, or related fields
Elegibilidade
Candidates with a Ph.D. or M.S. in a relevant technical discipline, or equivalent experience, who have strong computer vision and deep learning expertise and can work collaboratively across teams.
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Onde você trabalhará

Descrição da vaga

Position overview

OMNIVISION is looking for an Algorithm Engineer to investigate, design, and refine advanced computer vision and deep learning methods for imaging-focused products and use cases.

What you will do

  • Carry out research, development, and tuning of computer vision and deep learning models for image-based applications, including object detection/recognition, video analysis, and image improvement.
  • Create and deliver new deep-learning-based algorithms and features for CMOS image sensors, aligned with product specifications.
  • Evaluate, test, and deploy algorithms within camera processing chains or embedded platforms.
  • Keep up with the latest academic and industry advances, and contribute practical ideas for solving vision and image-quality problems.

Experience and qualifications

  • Ph.D. or M.S., or equivalent hands-on experience, in Electrical Engineering, Computer Science, Computational Imaging, Applied Mathematics, or a closely related discipline.
  • Strong familiarity with computer vision and deep learning, including areas such as recognition, tracking, or 3D reconstruction; exposure to image sensors, ISP workflows, color science, or image quality measurement is advantageous.
  • Demonstrated track record of independent algorithm research, supported by solid mathematical ability.
  • Comfortable coding in C/C++ and Python, with working knowledge of deep learning frameworks.
  • Clear communicator who can work effectively with cross-functional teams.

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