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(Sr./Staff) Algorithm Engineer (Computer Vision)
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.
- Retomar
- Obrigatório candidatar-se
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.