As a Machine Learning Instructor, you will teach students the mathematical foundations and practical applications of machine learning. The curriculum covers regression, classification, clustering, ensemble methods, deep learning, and model deployment. Students will work with real datasets and learn to evaluate, tune, and productionize ML models.

• 01Teach machine learning algorithms and their mathematical foundations
• 02Guide students through end-to-end ML pipelines: data collection, cleaning, training, evaluation
• 03Design and maintain lab exercises using real-world datasets
• 04Instruct on model selection, hyperparameter tuning, and cross-validation
• 05Cover deployment strategies for ML models in production environments
• 06Assess student competency through projects and practical examinations
• 07Maintain instructional facilities used for training and ensure the safety of students
• 08Research and recommend learning systems
• 09Conduct specific training for the trainee
• 10Give projects to students to test what has been learned
• 11Evaluate the effectiveness of each training session

• 01Minimum 2 years of hands-on experience with machine learning
• 02Strong foundation in statistics, linear algebra, and probability
• 03Proficiency in Python (pandas, NumPy, scikit-learn)
• 04Experience with model deployment (Flask, FastAPI, or cloud ML services)
• 05Excellent teaching and communication skills
• 06BSc/HND in Computer Science, Computer Engineering, Mathematics or its equivalent
• 07Knowledge of front-end languages and libraries (e.g. HTML/CSS, JavaScript)
• 08Graphics skills will be an added advantage (Photoshop or CorelDraw)
• 09Excellent written and verbal communication skills
• 10Good organization and multi-tasking abilities
• 11Post NYSC experience in teaching will be an added advantage

• 01Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or related field
• 02Industry ML certifications are a plus
• 03Prior teaching or training experience preferred