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

OMNIVISION

Singapore دوام كامل

كن أول من يتقدم بطلب

خبرة
أي
مرتب
الوظائف الشاغرة
1
تم النشر
لا مزيد من التفريغ
Work mode
في المكتب
تعليم
Ph.D./M.S. in Electrical Engineering, Computer Science, Computational Imaging, Applied Mathematics, or related fields
Eligibility
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.
Resume
Required to apply

Where you'll work

المسمى الوظيفي

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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