We are looking for a passionate student to help us develop state-of-the-art AI solutions for ADAS use cases, targeting mobile platforms such as passenger cars, trucks or motorcycles. In this role you will: Design and train neural networks (e.g. vision / radar / lidar / language / multi-modal) for various ADAS use-cases such as object detection, lane detection, scene classifiers, path planning, etc.
Design / update / maintain various “classical” 2D/3D (i.e. rule-based) computer vision algorithms Test and evaluate semantic KPI performance as well as HW efficiency of trained networks / CV algorithms Implement and test various visualization (2D/3D) methods to analyze performance of CV/AI algorithms Work with Cloud pipelines for model training and real-time target environments for model deployment Contribute to various parts of the data lifecycle, ranging from data ingestion, to selection, curation and preparation for training/evaluation Technology stack: Python (and most used ML libraries) Pytorch Azure Databricks Version source control (e.g. Git, Bitbucket) OpenCV C++ CUDA Matlab Docker Visual Studio Linux Unity & Blender C#
Требования: AI/Machine Learning/Deep Learning Algorithms and Data structures Embedded programming in real-time environments Data Visualization Data preprocessing Image / Signal Processing Object Oriented Programming Probability theory & Statistics 2D & 3D Geometry Logical and Analytical thinking The languages you should know: English – a good level is manda