Intern, Artificial Intelligence (Winter 2026)

During your internship, you will contribute to:

• Support feature engineering activities over given data for training models.
• Developing and optimizing Python scripts for data processing and automation.
• Collaborating with experienced Machine Learning Engineers (MLEs) and Data Engineers to develop and deliver solutions.
• Experimentation with different cloud services related to artificial intelligence.
• Deploying your solutions and monitoring their performance.
• Troubleshooting and optimizing Data Science pipelines and ML solutions.
• Researching and developing Machine Learning models with the supporting data infrastructure.
• Developing, maintaining, and optimizing data flows using leading cloud solutions like Databricks.
• Applying best practices in software development and using a DevOps framework for continuous integration and deployment (CICD) of data solutions.
   

During your internship, you will learn:

• The architecture and operation of a modern Machine Learning platform.
• Principles of software development with DevOps, MLOPS and CICD methodology.
• Fundamentals of cloud data solutions and AI services.
• Converting business requirements into technical and analytical solutions.
• Communication between business unit users, solution architects, data scientists, and developers.
• Methods for testing, validating, and deploying data and ML solutions into production.
• Key security elements in the development of data and ML solutions.
• The importance of data governance to accelerate the delivery of data and AI solutions.
• Approaches to feature engineering, model experimentation, and operationalization of ML models.

How to thrive in this role?

• You are enrolled in an undergraduate (final year) or graduate university program in computer science, engineering, or other applied science programs.
• You master Python scripting.
• You have a willingness to learn new technologies and approaches in ML and data engineering.
• You are a team player who communicates effectively.
• You can demonstrate good level of autonomy in the execution of your project.
• You are a problem-solver and a solution proposer.
• Familiarity with optimization techniques is an asset.
• Experience with feature engineering and machine learning model development is an asset.
• Ability to communicate fluently in French and English.