Instructor – Applied Artificial Intelligence Program

MSM UnifyNationwideroam-ngpublished 09/17/2026
Must-have:PythonGitAWSAzureGoogle CloudDockerKubernetesCloudDataCI/CDAI

The Applied Artificial Intelligence Instructor will deliver technical instruction for the AEC LEA.E7 – Intelligence artificielle appliquée program.

The ideal candidate combines strong practical experience in artificial intelligence, machine learning, data science, software development and/or MLOps with the ability to explain complex concepts in a clear and accessible manner.

The instructor may be assigned one or multiple courses according to their technical specialization.

Key Responsibilities

  • Deliver engaging AI and technology instruction in French.
  • Communicate effectively in English with administration and when using technical documentation and resources.
  • Develop lesson plans, presentations, demonstrations, practical labs and assessments.
  • Teach both theoretical concepts and practical AI implementation.
  • Guide students through AI, machine learning and data projects.
  • Demonstrate real-world AI applications and industry use cases.
  • Teach students how to develop, test and deploy AI solutions.
  • Evaluate assignments, projects, examinations and practical exercises.
  • Provide constructive feedback and academic guidance.
  • Keep course content aligned with current AI industry developments.
  • Incorporate current tools, frameworks and methodologies into instruction.
  • Support students in developing employment-ready AI and data skills.
  • Participate in curriculum development and faculty meetings.
  • Maintain student records and submit grades/evaluations as required.
  • Deliver instruction effectively in an online environment.

Potential Courses / Subject Areas

Depending on specialization, the instructor may teach:

  • Fundamentals of Artificial Intelligence
  • Introduction to Programming
  • Python programming
  • Data preparation and analysis
  • Data cleaning and preprocessing
  • Exploratory data analysis
  • Data visualization
  • Supervised machine learning
  • Regression and classification
  • Unsupervised machine learning
  • Clustering
  • Dimensionality reduction
  • Anomaly detection
  • Deep learning
  • Neural networks
  • Natural language processing
  • Computer vision
  • Reinforcement learning
  • AI agents and intelligent workflows
  • Industrial applications of AI
  • AI automation
  • AI solution development
  • Model deployment
  • MLOps
  • Cloud-based AI deployment
  • Model monitoring and production environments

Required Qualifications

Bachelor's degree or equivalent in:

  • Computer Science
  • Artificial Intelligence
  • Data Science
  • Machine Learning
  • Software Engineering
  • Computer Engineering
  • Mathematics/Statistics
  • or a related technical discipline.

Master's degree preferred for advanced AI, machine learning, deep learning and reinforcement learning subjects. Minimum 3 years of relevant professional industry experience . 4–5+ years preferred for advanced ML, Deep Learning and MLOps instruction. Demonstrated hands-on experience developing or deploying AI/ML solutions. Strong understanding of modern AI and machine learning methodologies. Fluent French and English – mandatory. Excellent communication and presentation skills. Ability to explain complex technical concepts to beginner and intermediate students. Ability to teach effectively in an online environment.

Technical Expertise

Depending on the position/course assignment, candidates should have experience with relevant technologies such as:

Programming

  • Python
  • SQL
  • Git/GitHub
  • APIs
  • Software development fundamentals

Data

  • Pandas
  • NumPy
  • Data preprocessing
  • Data analysis
  • Data visualization
  • Power BI / Tableau

Machine Learning

  • Scikit-learn
  • Regression
  • Classification
  • Clustering
  • Model evaluation
  • Feature engineering

Deep Learning

  • PyTorch
  • TensorFlow
  • Neural networks
  • NLP
  • Computer vision

AI

  • Generative AI
  • LLMs
  • AI agents
  • Intelligent automation
  • AI applications

MLOps / Cloud

  • MLflow
  • Docker
  • Kubernetes
  • CI/CD
  • AWS / Azure / Google Cloud
  • Model deployment and monitoring

Preferred Certifications

Relevant certifications are an asset, including:

  • AWS Machine Learning / AI certifications
  • Microsoft Azure AI certifications
  • Google Cloud AI/ML certifications
  • Databricks certifications
  • NVIDIA AI certifications
  • TensorFlow certifications
  • Other recognized AI, data science or cloud certifications