ADS Machine Learning Data Scientist

The Autonomous Driving Software (ADS) Development team in Hyundai America Technical Center, Inc. (HATCI) is an engineering and data science team that focuses on improving performance and expanding ADAS/AD features and services of Hyundai/Kia/Genesis vehicles for the North American (NA) market. The team’s key roles and responsibilities are: • New Technology Introduction to spearhead new technology conceptualization for future generation ADAS/AD experiences for the NA market through in-house development as well as strategic partnerships with key technology hubs such as universities, startups and research labs • Software Development to expand Hyundai/Kia/Genesis ADAS/AD capabilities in coordination with the R&D Headquarters and other internal/external project partners • Prototyping and Demonstration to develop prototypes and proof of concept demonstrations to various global teams within Hyundai Motor Group (HMG) for new ADAS/AD functions targeted for the NA market • Software Strategy and Planning to identify market trends and customer needs for key ADAS/AD experience themes and selection of new concept ideas • Data Collection and Curation for Production Applications to support development of data-driven machine learning models with NA data. We are looking for a talented and curious Machine Learning Data Scientist with a focus on computer vision and deep learning to help us drive innovation in the ADAS space. Key Responsibilities: • Design, train, and evaluate machine learning (ML) models for perception tasks such as object detection, classification, and segmentation using real-world as well as synthetically generated data • Work with large-scale datasets, perform data curation, annotation analysis, and data-driven error diagnosis • Develop or improve automated data annotation pipelines leveraging ML and active learning strategies • Design and evaluate experiments involving synthetic and real-world data mixing, including ablation studies to assess the impact of data and architecture choices • Collaborate with other engineers to deploy models on embedded hardware (e.g., NVIDIA Jetson, TDA4 EVB) • Conduct empirical studies and ablation experiments to improve performance through data selection, augmentation, and annotation strategies, rather than architectural complexity, to support vision AI workflows • Stay up to date with the latest research and trends in computer vision and ML, especially in the autonomous driving domain Preferred Qualifications: • MS or PhD level education in Engineering or Computer Science with a focus on Deep Learning, Artificial Intelligence, Computer Vision or a related field or commensurate work experience • Experience with data annotation workflows and auto-labeling tools; knowledge of annotation standards for computer vision tasks • Experience analyzing and optimizing ML model performance through data analysis (e.g., mining edge cases or hard negatives, dataset balancing)