Computer Vision Systems (algorithm) Engineer Full-time

Company:
Qualcomm India Private Limited

Job Area:
Engineering Group, Engineering Group > Systems Engineering

General Summary:

Qualcomm is the innovation leader in the area of integrated chipsets that power advanced mobile devices. We are building on and expanding our reputation as the industry powerhouse for innovation in both wireless technologies and enabling advanced multimedia capabilities. Join Qualcomm India and become part of the growing multimedia systems team that innovates to bring the higher performance on mobile multimedia capabilities at the lowest power consumption and device cost, while providing the strongest feature differentiation. The team creates embedded imaging solutions for Snapdragon chipsets that power advanced mobile, automotive, IoT, and AR/VR devices. Successful candidates will be part of a systems and R&D team that develops embedded camera and imaging solutions, image signal processor (ISP), video codec hardware as well as advanced algorithms for computer vision and image/video processing. Responsibilities:

The job responsibilities may include a subset of the following:

• Develop and/or optimize depth estimation and optical flow algorithms, enabling critical use-cases across mobile, AR/VR and automotive platforms

• Research and develop power-efficient computer vision algorithms, deep learning architectures and models in computer vision for AI-enabled camera, video, AR/VR products
• Developing or Optimizing image processing and computer vision algorithms for HW acceleration
• Support product teams for commercialization, such as solution optimization, performance profiling and benchmarking.

Required qualifications:

• Bachelors + 3yrs relevant experience, Master’s + 2yrs relevant experience or PhD degree in Electrical Engineering, Computer Science, and/or closely related field
• Background in digital image processing and computer vision fundamentals
• Background in depth estimation and optical flow algorithms
• Working knowledge with OpenCV and vision algorithms (feature detection/description and matching)
• Strong knowledge in data structures and working experience with C/C++ programming

Preferred qualifications

• Experience developing practical deep learning algorithms using PyTorch, TensorFlow
• Academic publications in computer vision research at top conferences and journals

Educational requirements:

Required: Bachelor’s in Computer science or Electrical & Computer Engineering

Preferred: Master’s or PhD in Computer science or Electrical & Computer Engineering

Keywords:

Computer vision, Machine learning, Image processing, Depth from stereo, Optical flow

Minimum Qualifications:
• Bachelor’s degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
OR
Master’s degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.

Applicants: If you need an accommodation, during the application/hiring process, you may request an accommodation by sending email to accommodationsupport

Although this role has some expected minor physical activity, this should not deter otherwise qualified applicants from applying. If you are an individual with a physical or mental disability and need an accommodation during the application/hiring process, please call Qualcomm’s toll-free number found here for assistance. Qualcomm will provide reasonable accommodations, upon request, to support individuals with disabilities as part of our ongoing efforts to create an accessible workplace.

Qualcomm is an equal opportunity employer and supports workforce diversity.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

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