Data Science AI Intern

# Data Science & AI Intern — AI Lab

## About Us

The [Canadian Food Inspection Agency (CFIA)](https://inspection.canada.ca) is the federal body responsible for safeguarding food, animals, and plants in Canada. Within CFIA, the **AI Lab** is a multidisciplinary team that designs and develops AI-powered digital tools to modernize inspection and regulatory processes. We work in the open (open source) and strive to deliver reliable, secure solutions.

🔗 [inspection.canada.ca](https://inspection.canada.ca) | [github.com/ai-cfia](https://github.com/ai-cfia)

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## General Information

• **Position:** Data Science & AI Intern — AI Lab
• **Location:** 2001, Robert-Bourassa Blvd, Montréal, QC H3A 3N2 — hybrid
• **Period:** Summer 2026 (May to August 2026, 4 months)
• **Schedule:** 37.5 hours/week, Monday to Friday
• **Salary:** TBD
• **Positions available:** 1

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## Position Context

The AI Lab builds intelligent tools that help CFIA inspectors and scientists make faster, more informed decisions. As a data science intern, you'll play a key role in the design, development, and deployment of advanced machine learning models and solutions on **Kubernetes**. You will work on applied AI/ML problems with real-world regulatory impact — from training and evaluating models to designing scalable data pipelines and ensuring smooth integration into production systems through **DevOps** practices.

Examples of projects you may contribute to:

• **[Nachet](https://github.com/ai-cfia/nachet)** — AI-powered seed identification system. Computer vision models classify seeds from digital microscope images to support inspection workflows. (Python, deep learning)
• **[FertiScan](https://github.com/ai-cfia/fertiscan)** — AI-powered label compliance analysis tool. Uses LLMs to extract and validate regulatory information from product labels. Expanding beyond fertilizers to other regulated product categories. (Python, LLMs/NLP)

_Additional projects may be added during Summer 2026._

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## Tasks

• **~40% Model Development & Experimentation** — Research, train, fine-tune, and optimize deep learning models (NLP, Computer Vision). Design and run experiments to improve accuracy and performance on domain-specific tasks.
• **~30% Data & ML Engineering Pipelines** — Build and maintain end-to-end machine learning pipelines on **Microsoft Azure**, using services like **Azure Machine Learning**, **Azure Databricks**, and **Azure DevOps**.
• **~20% Analysis, Deployment & Integration** — Preprocess data, perform feature engineering, and evaluate model robustness. Collaborate with full-stack teams to integrate ML capabilities into applications, ensuring a seamless user experience.
• **~10% Collaboration & DevOps** — Apply DevOps best practices for automated training, deployment, and monitoring. Participate in code reviews, stand-ups, and stay updated on the latest trends in Azure and ML technologies.

_The balance shifts depending on project needs and the intern's interests._

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## Skills & Requirements

### Required

**Education:**

• Graduate student (Master's or PhD) in Machine Learning, Data Science, Computer Science, or a related field

**Technical skills:**

• Python (NumPy, pandas, scikit-learn)
• Experience with deep learning frameworks (**PyTorch**, **TensorFlow**, or **Keras**)
• Solid understanding of **NLP** or **computer vision** techniques
• Experience in designing and implementing ML solutions with a focus on deep learning
• Git and GitHub

**Interpersonal skills:**

• Self-driven and technically curious
• Clear communication (written and verbal)
• Ability to work in a team in a hybrid environment
• **French or English required** (bilingualism is an asset)

### Nice to Have

• Experience with LLMs (fine-tuning, prompt engineering, RAG)
• Proficiency with **Microsoft Azure** services, including **Azure Machine Learning**, **Azure Databricks**, **Azure DevOps**, **Azure Kubernetes Service (AKS)**, and **Azure Data Factory**
• Practical experience with **DevOps** practices: **CI/CD pipelines**, **containerization** (e.g., Docker), and **Infrastructure as Code** (e.g., Terraform)
• Experience in **full-stack web development**
• Knowledge of MLOps (experiment tracking, model serving, performance monitoring)
• Publications or contributions to open source ML projects

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## Work Environment

• Agile and collaborative environment with direct mentoring from team members
• Collaboration tools: **GitHub**, **Microsoft Teams**
• Regular code reviews and knowledge sharing

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# Stagiaire Science des données et IA — AI Lab

## Description de l'entreprise

L'[Agence canadienne d'inspection des aliments (ACIA)](https://inspection.canada.ca) est l'organisme fédéral responsable de la sauvegarde des aliments, des animaux et des végétaux au Canada. Au sein de l'ACIA, le **AI Lab** est une équipe multidisciplinaire qui conçoit et développe des outils numériques propulsés par l'intelligence artificielle pour moderniser les processus d'inspecti