Canadian National Railway Company (CN) is looking for a highly motivated person to fulfill a full-time (40h/week) Intern, Data Scientist – Computer Vision  position in Montreal, QC from May - Aug 2025.

Job Summary

The Intern, Data Scientist – Computer Vision is responsible for working on CN’s Automated Train Inspection (ATI) program and support the development and evaluation of the Machine Learning (ML) and Computer Vision pipeline. The incumbent assists with the automation of the image annotation process and explores training of neural networks leveraging small datasets. The position ensures consistency across image annotations for the ML and Deep Learning (DL) models training.

Major Responsibilities

· Perform research on efficient learning algorithms that require fewer manually labeled data sets such as Active Learning, Semi-Supervised learning, and Few-Shot Learning

· Publish research findings to ML conferences might be a possibility

· Support Data Scientist and ML Developer on the design and development of ML Solutions

· Translate the technology solution architecture into engineering and software development standards and specifications

· Apply and ensure compliance with appropriate CN Information and Technology (I&T) standards, including Security, Architecture, Project Delivery Methodology, Sarbanes-Oxley (SOX), Telecom, and Software Engineering

· Conduct code reviews and ensure coding standards

Requirements

· Experience with Python, Shell, and other scripting languages

· Knowledge of DL frameworks such as Pytorch, Tensorflow, and Keras

· Knowledge of Computer Vision for Objects Detection, Segmentation, and Classification

· Applies critical thinking

· Communicates with impact

· Solves problems to create value

· Experience in Active Learning, Semi-Supervised Learning, and Few-Shot Learning algorithms*

Education

· Working toward a Bachelor’s Degree, Master’s Degree or Ph.D. Degree in Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence (A.I.), ML or a related field of study

*Any experience/education/skills/knowledge for these above would be considered as an asset