About PAVE (Who We Are) PAVE is on a mission to use AI to revolutionize digital vehicle inspections. We leverage state-of-the-art computer vision and machine learning solutions to power thousands of inspections daily, helping businesses and individuals achieve faster, more accurate, and sustainable vehicle assessments. The PAVE product provides a wide variety of AI use cases. These include, but are not limited to, moderation systems for captured content, optical character recognition, image recognition With segmentation and object detection models, depth estimation and anomaly detection as well as systems for monitoring of data privacy. Our globally distributed team includes AI researchers, ML engineers, product specialists, and software engineers in both Vietnam and Canada. Role & Impact As a Computer Vision Engineer, you will collaborate with cross-functional teams focused on developing proprietary solutions to design and train computer vision solutions that streamline and automate vehicle inspections at scale. What You’ll Work On You’ll help develop Deep Learning systems for depth estimation, feature matching, homography estimation and segmentation based on our unique vehicle inspection datasets. Professional Qualifications Technical Expertise: In-depth knowledge and experience in deep learning for computer vision use cases using PyTorch. Has a strong desire to drive innovation by staying current with industry trends and incorporating new technologies into projects. Preferred Attributes: Experience in developing depth estimation and segmentation models with deep neural networks. More than 3 years of experience with training models using PyTorch. Minimum Bachelor's degree in Computer Science or similar, Master's preferred. Excellent communication and collaboration skills We thank all interested applicants. Only candidates selected for an interview will be contacted.