Description:
The ADAS Machine Learning intern will assist the Autonomous Driving Software perception engineers with building AI/ML models for vision-based perception models for autonomous driving applications tailored for the North American market
HATCI Autonomous Driving Software Department is seeking ADAS Machine Learning interns who are interested in acquiring hands-on experience processing large-scale datasets to support training of Deep Neural Network models for perception model development, mostly focused on object detection, classification and depth estimation tasks. You will assist the Autonomous Driving Software team with building ML models by processing and curating large-scale sensor data (e.g cameras, LiDAR, IMU)
What you will do:
- Help with vision-based data curation and labeling tasks for training deep neural network perception models
- Support test vehicle instrumentation and data acquisition tasks
- Develop data engine processes to streamline ML workflows from data acquisition all the way to model training and evaluation
- Assist evaluating and developing new ML models particularly focusing on object detection, tracking and classification
Qualifications:
- Currently pursuing a full-time engineering degree with a focus on computer science, machine learning, computer vision or a related field
- Knowledge of fundamentals in data analysis and exposure or willingness to learn or expand their knowledge machine learning workflows
- Curiosity and a willingness to learn large-scale data processing for building environment perception models for assisted / autonomous driving software development
- Experience programming in Python, C++, Matlab or similar
Hyundai America Technical Center, Inc. (HATCI) is an equal opportunity employer commited to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status, other protected veteran status, and any other protected class under law.
