AI Algorithm Expert - Hand Tracking, Pico

About the Team The team at Pico is dedicated to leverage technologies such as computer vision, deep learning, SLAM, 3D reconstruction, and multi-sensor fusion, we continuously expand the ways humans interact with the virtual world through handheld controllers, bare-hand tracking, eye-tracking, and XR interactive accessories, enhancing the overall interaction experience. Responsibilities： - Lead the development of high-precision and low-latency hand tracking algorithms in XR scenarios, covering directions such as monocular/multiple vision and multi-sensor fusion - Build a robust 3D gesture pose estimation model to solve the problems of extreme scenarios such as occlusion, fast motion and complex illumination - Optimize the real-time inference performance of the algorithm on the mobile XR headset to achieve millimeter-level tracking accuracy - Lead the construction of the Multi Modal Machine Learning interaction algorithm framework (hand + eye movement + peripheral device) to create a natural XR interaction pattern - Promote patent layout and publication of papers in top conferences (CVPR/ICCV/SIGGRAPH, etc.)

to enhance the technical influence of the team

Minimum Qualifications:

- Majored in Computer Vision, Pattern Recognition or Applied Mathematics, with more than 5 years of experience in algorithm R&D - Familiar with the technical principles, advantages and disadvantages of commercial solutions such as ARKit Hand Tracking and Quest Hand Tracking - Proficient in PyTorch framework and QNN deployment ecosystem, with practical experience in Tensor

RT end-side optimization

Preferred Qualifications:

- Experience in developing the core algorithm of Hand Tracking for XR products such as Apple Vision Pro, Meta Reality Labs, and Magic Leap - Published papers on gesture tracking in top conferences such as CVPR/ICCV/SIGGRAPH