Responsibility:

a. Study and develop cutting-edge techniques in computer vision, visual odometry, machine learning, and perform in-depth analysis and optimization to ensure the best possible performance on mobile GPU architectures..
b. Collaborate closely with Visual SLAM engineer and AI research groups to apply the latest technology to autonomous vehicle system.
c. Apply and optimize 3rd party algorithms/models

Minimum qualifications:

a. MS or Ph.D. in Computer Science, Electrical Engineering, or a related technical field.
b. Experience with data-parallel and/or GPGPU programming, OpenCL/Vulkan and/or CUDA.
c. Familiar with memory hierarchy of GPU, including coalesced memory access, bank conflict & subgroup operations.
d. Strong engineering practices, debugging/profiling skills, familiarity with multi-threaded programming.
e. Experience developing algorithms in Robotics, Computer Vision and/or Machine Learning.
f. Experience in the field of computer science, with experience in data structures, algorithms and software design.
g. Familiar with C++ Standard Template Library.

Preferred qualifications:
a. Proficient at surveying papers and implementing mathematical equations with the ability to interpret equations and derive own variants.
b. Experience in implementaiton & optimization of image processing, object tracking and feature extraction/detection algorithm on Mobile GPU.
c. Experience in autonomous driving is a strong plus.