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(Sr./Staff) Algorithm Engineer (Computer Vision)
Singapore · مکمل وقت
درخواست دینے والے پہلے فرد بنیں۔
- تجربہ
- کوئی بھی
- تنخواہ
- —
- کھلنا
- 1
- پوسٹ کیا گیا
- 1 گھنٹہ قبل
- Work mode
- دفتر میں
- تعلیم
- 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
ملازمت کی تفصیل
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.