Working student Deep Learning & Data Science
Core
Design and train neural networks and classical computer vision algorithms for ADAS use cases like object detection, lane detection, and path planning on mobile platforms.
Role type
Deep Learning & Data Science Working Student
Builds
AI solutions for ADAS targeting passenger cars, trucks, and motorcycles
Domain
Automotive / Automated Driving Systems
Deliverable
production ML models
Required skills
Neural network design and training, Computer vision (2D/3D), Data lifecycle management, Cloud pipeline implementation, Model evaluation and testing
Preferred skills
Embedded programming in real-time environments, Data visualization, Image/Signal processing, Probability theory & Statistics, 2D & 3D Geometry
Technologies
Python, PyTorch, Azure, Databricks, Git, OpenCV, C++, CUDA, Matlab, Docker, Linux, Unity, Blender, C#
Responsibilities
Design and train neural networks for various ADAS use-cases, Maintain classical 2D/3D computer vision algorithms, Test and evaluate semantic KPI performance and HW efficiency, Implement visualization methods to analyze algorithm performance, Work with Cloud pipelines for training and deployment, Contribute to data ingestion, selection, curation, and preparation