- Serve as the technical authority for pixel reconstruction algorithms, influencing imaging architecture decisions across ISP, sensor, optics, and AI imaging pipelines, and driving improvements in end:
user perceptual video quality and overall camera experience.
- Collaborate closely with cross:
functional teams to develop proposals for next:
generation imaging solutions in the domain of pixel reconstruction, addressing customer requirements and limitations of existing approaches
- Define and drive the roadmap for core computational imaging algorithms (e.g., denoising, super:
resolution, bokeh, multi:
frame fusion), ensuring continuous product competitiveness in image quality and user experience
- Propose efficient HW IP / SoC architecture solutions through detailed analysis of power, performance, area, latency, and image quality trade:
offs
- Lead the end:
to:
end validation of pixel reconstruction innovations, from concept exploration and simulation to prototype implementation and performance benchmarking, guiding the overall algorithm development strategy
- Continuously evaluate and integrate state:
of:
the:
art algorithms relevant to embedded imaging systems, image processing, and video processing
- Mentor senior engineers and collaborate across global multidisciplinary teams, including ISP architecture and design, sensor development, and product engineering.
Requirements
- Master's or PhD degree in Electrical Engineering, Computer Vision, Computational Imaging, or a related field, with 15+ years of industry experience in mobile imaging systems.
- Deep expertise in mobile imaging systems and camera module design, including image sensors, optics, mechanics, auto:
focus systems, optical image stabilization, and both software and hardware image processing pipelines
- Proven experience designing and deploying modern computational imaging algorithms, such as denoising, super:
resolution, bokeh/depth rendering, and multi:
frame image fusion
- Strong experience optimizing imaging algorithms for embedded hardware platforms, considering constraints such as power consumption, performance, memory bandwidth, silicon area, and latency
- Demonstrated leadership experience, including mentoring senior engineers and driving cross:
functional collaboration across globally distributed teams.
