Responsibilities

Contribute to projects developing 2D image and 3D point cloud models for object and panoptic detection, focusing on urban and roadway features like traffic lights, utility poles, curbs, and painted road markings.
Develop prototypes to detect paint lines and curbs on roadways.
Bring perception models and algorithms into real-time detection for edge mapping hardware, trading accuracy for speed.
Assist in development and tuning of machine learning models to enhance performance and accuracy.

Requirements

Strong programming fundamentals in Python, algorithmic problem-solving, and clean code design.
Ability to implement and iterate on heuristic or geometry-based algorithms quickly.
Hands-on experience with machine learning frameworks (e.g., PyTorch, Jax) and computer vision tasks.
Interest in applying machine learning to geospatial data analysis.
Excellent problem-solving abilities and collaborative mindset.
Currently pursuing a degree in Machine Learning, Computer Science, or related field, with solid understanding of ML concepts.