ML Engineer

As an ML engineer, you will be responsible for utilizing TensorFlow for object detection, road environment recognition, depth/motion estimation, vehicle control, etc., and be responsible for modeling, learning, evaluation, and development of the model. Additionally, you will be involved in the development of major development tasks such as Segmentation, 3D Vehicle Detection, VRU Detection, Debris Detection, General Object Detection, stereo/mono depth estimation, optical flow estimation, object tracking, path prediction, etc. You will use Python and C/C++ as development languages, and utilize TensorFlow as an OS for Windows and Linux, as well as Docker and GCP, to apply the latest technology and contribute to the safety improvement of autonomous vehicles.

・Utilization of TensorFlow and ML frameworks for model implementation and evaluation ・Minimum required fundamental statistics and mathematical knowledge for ML and Computer Vision ・Skills to easily perform image data processing and analysis using Python ・Experience in image or Lidar recognition algorithm development

・Experience in programming with C/C++ for sensor fusion ・Experience in modeling, learning, and management of march test verification ・Seeking experience in data augmentation, Teacher-less learning, and other techniques to improve generalization ・Experience in developing ML models as prototypes and services ・Experience in quantize, pruning, network architecture search, etc., for optimization on ML models ・Experience in optimizing ML models for semi-custom devices such as FPGA ・Experience in presenting at international academic conferences such as CVPR ・Experience in high-ranking competitions such as Kaggle