About the job
We are seeking an individual to conduct advanced engineering in 3D perception and machine learning to address challenges in automated driving.
Responsibilities
Design and extend state-of-the-art machine learning models, for specific ADAS applications.
Create and curate internal datasets.
Adapt existing models trained using public datasets to use internally generated data.
Perform large-scale data processing.
Perform basic data mining.
Evaluate and document model performance of different methods.
Qualifications
Minimum
Currently pursuing a Masters or Ph.D in Computer Science or Engineering
1+ years of research and engineering experience for computer vision and machine learning algorithms (e.g. DNN, RNN, GNN, GAN, ViT, etc).
1+ years of research and engineering experience working with VLM/LLM architectures.
Knowledge of automated driving software stack components (e.g. Perception and Localization).
Programming experience in Python and C++, and hands-on experience with libraries such as PyTorch and OpenCV.
Demonstrated willingness and ability to learn and grasp new concepts quickly.
Self-starter and self-motivated.
Minimum GPA of 3.0
Preferred
Experience working with open-source autonomous driving datasets.
Experience with geographic data (WGS84/UTM).
Experience working with various sensor modalities including cameras and LiDAR.
Experience developing deep learning architectures and performing model optimization.