1. Improve model accuracy/performance to achieve real-time inference on edge
device.
2. Iterate model to cover all kinds of common features on highway/city scene.
3. Develop a single model to simultaneously output object detection and
segmentation result.
4. Apply model distillation, pruning, factorization, and quantization.
5. Data cleaning and augmentation.
6. Port to edge device, profile and find bottlenecks.
7. SOTA paper reading and implement, model zoo building.
1. Experience in CNN model training, especially on object detection and semantic segmentation.
2. Familiar with cost function rewritten and hyper parameters tuning.
3. Hands-on experience in deep learning framework, e.g., Pytorch, Tensorflow or Caffe.
4. Solid experience in system design and programming, ability to work with big data with minimal engineering support.
市民大道六段288號10樓之9
新馳科技是由一群對自駕車充滿熱忱並曾經任職於全球知名企業的專業人員所共同成立。我們提供讓對於自動駕駛技術有興趣與熱情的研發人才一個實踐所長的舞台。
我們有良好工作環境與福利制度，重視與我們一起成長的員工，不管是技術或專業上的成長提升，公司提供專業的學習及個人成長的空間，歡迎對自駕車懷有夢想抱負的人才，與有相關視覺AI或自駕車開發經驗的優秀工程師朋友，一起加入我們新馳科技團隊的行列。
讓我們透過專業與熱情，一起發展應用科技於未來自駕車產業。