Senior Computer Vision Software Engineer

SK Hynix
SK Hynix

Job Overview

With time, CMOS image sensor (CIS) technology has evolved with dramatic improvement over the years. Finding usage in variety of applications such as mobile devices, IoT devices and robotics, it is now feasible to integrate computer vision and machine learning into a single CMOS chip at an attractive cost/performance point.As SK hynix America, a research facility in San Jose, we are building a CIS Research and Development team located in San Jose R&D campus. In bringing great talent together, we are building a team of pathfinders to new technological developments in computer vision processor designs and AI hardware accelerators for next-generation CMOS Image Sensors.With SK hynix America CIS team, you will work on state-of-the-art edge device computer vision. As a founding member of the team, you will have much freedom in initiating projects, and you will be working with highly motivated team members in a start-up environment.Responsibilities:* With strong technical background, this position should lead and/or perform architect, design and development of classical and deep learning base computer vision pipelines.* With a start-up mindset, this position requires hands-on implementation of the computer vision architectures. This positions must work closely with HW team, and sensor design team to optimize the computer vision pipeline to the specific sensors.* Focuses are design of computer vision pipeline for object detection, object recognition, object tracking, and depth sensing but not limited to these pipelines.* This position may need to build the development environment if it is necessary.Requirements:* PhD degree in Computer Engineering, Electrical Engineering, or related degree with 5+ years of CMOS industry experience.* Master’s degree with 10+ CMOS industry experience* Experience in working with HW team to optimize the computer vision pipeline to reduce power, chie area, and memory BW.* Experience in optimizing DNN model parameters to reduce memory size.* Experience in computer vision architecture.* Experience in computer vision algorithm with both classical method and deep learning base method.* Deep understanding in computer vision chip architecture.* Proficient in C++, Python, Tensorflow, Caffe.* Start-up mindset.

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