XPeng Motors is one of China’s leading smart electric vehicle (“EV”) companies. We design, develop, manufacture and market smart EVs that are seamlessly integrated with advanced Internet, AI and autonomous driving technologies. We are committed to in-house R&D and intelligent manufacturing to create a better mobility experience for our customers. We strive to transform smart electric vehicles with technology and data, shaping the mobility experience of the future.
We are looking for machine learning research engineer with strong programming and development skills and experience with machine learning. Experiences with deep learning algorithm, 3d reconstruction, SLAM, unsupervised/self-supervised or active learning are preferred.
Our mission is to solve the autonomous driving problem. You will work with a team of machine learning researchers to build AI software systems, learn about deep learning algorithms, and use your technical skills to advance autonomous driving.
Improve qualities of 3d reconstruction/detection algorithms using millions of real-world sensor data (lidar, radar, hd-map, CAN bus and video) on complex street-view scenes.
Improve feature qualities training on large unlabeled, semi-label multi-task dataset.
Writing efficient code to train deep neural network, processing data, visualization, and debug optimization process.
Experiences in PyTorch or Tensorflow.
Fluent Python coding, parallel coding, metrication, testing and version control.
Solid understanding of literature and capable to apply state-of-the-art algorithm to solve computer vision challenges.
Experiences with deep learning algorithm, 3d reconstruction, SLAM, unsupervised/self-supervised or active learning are preferred.
What do we provide:
A fun, supportive and engaging environment.
Opportunities to pursue and work on cutting edge technologies
Snacks, lunches and fun activities
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other proscribed category set forth in federal or state regulations.