• Translate product feature requirement to Al-based software solution.
• Design end-to-end workflow from Machine learning model architecture design, data acquisition methodology, training, and trained model deployment on actual hardware.
• Provide assessment on algorithm performance as well as target hardware specification and relevant required resources. Target application relates to object detection using image/video information.
• Work closely with hardware team in order to integrate hardware-software solution.
• Domestic and international travel support if needed during the product development cycle.

• 0-3+ years of industrial experience in computer vision, machine learning, deep learning, reinforcement learning, and algorithm design.
• Strong programming skills with Python and C/C++.
• Understand model implementation at the hardware level, i.e. edge computing unit, GPU, cloud network.
• Strong background in computer vision theory, optics and image signal processing.
• Teamwork mindset.
• Excellent English communication and well-organized documentation.
• Preferred Qualification
• Intensive experience in the applications of facial recognition, object detection, lane line detection, traffic sign classification, and scene understanding. Intensive hands-on experience of machine learning model deployment at a hardware level. Experience in motion sensor implementation, i.e. gyroscope, accelerometer, magnetometer. Experience in Video stabilization algorithm design and implementation, as well as Image signal processing pipeline — auto exposure, HDR, noise reduction, and multiple image fusions, depth map generation, and 3D localization/mapping.

• B.S./B.Eng./M.S./Ph.D. in computer science, computer engineering or electrical engineering with 0-3 years of industrial experiences.

Hardware startup focusing on the integration of product design, custom hardware design, and state-of-the-art machine learning solution. Our team has solid industrial experiences with professinal mindset, collaborative teamwork environment, and accpets challenges to create great consumer electronics products.