Teaching Assistant - AI/ML | Part - Time | Odia

About the Opportunity

Masai School, in academic collaboration with a premier institute, is looking for an experienced Teaching Assistant – Artificial Intelligence & Machine Learning to support learners enrolled in an online AI/ML program.

As a Teaching Assistant, you will work closely with learners to help them understand AI/ML concepts, solve technical doubts, debug code, and apply their learning through practical projects.

This is a great opportunity for AI/ML professionals who enjoy teaching, mentoring, problem-solving, and helping others build strong technical foundations.

Institution: Masai School, in academic collaboration with a premier institute
Program: Artificial Intelligence & Machine Learning
Time Commitment: 6–8 hours per week

Key ResponsibilitiesTeaching & Doubt Resolution

• Conduct weekly doubt-solving and tutorial sessions in Odia.

• Help learners understand AI/ML concepts, Python programming, and machine learning workflows.

• Simplify complex technical concepts using practical examples.

• Support learners with coding challenges, assignments, and AI/ML projects.

• Help learners troubleshoot and debug Python and ML implementations.

Technical & Academic Support

• Guide learners on data preprocessing, feature engineering, model selection, training, and evaluation.

• Support learners with Supervised and Unsupervised Learning concepts and algorithms.

• Help learners understand and implement ML models using Scikit-learn, PyTorch, or TensorFlow.

• Guide learners in understanding model performance and improving their ML solutions.

• Help learners understand basic model deployment and production workflows.

Project & Industry Support

• Help learners build practical AI/ML projects and portfolios.

• Review learner code, notebooks, assignments, and projects.

• Provide actionable technical feedback to improve project quality.

• Share real-world AI/ML use cases and industry practices.

• Guide learners on standard ML tools, libraries, workflows, and development practices.

• Help learners understand concepts such as model evaluation, feature engineering, overfitting, optimization, and deployment.

Learner Engagement

• Provide regular feedback and technical guidance to learners.

• Encourage learners to actively participate in sessions and discussions.

• Track learner progress and highlight technical challenges to the academic team.

• Support learners in completing projects and overcoming technical blockers.

• Contribute feedback to improve the learning experience and course delivery.

Candidate Requirements Must Have

• 2+ years of hands-on experience in Artificial Intelligence / Machine Learning.

• Strong Python programming skills.

• Good understanding of:

  • Data preprocessing and feature engineering

  • Supervised and unsupervised learning

  • ML algorithms and model evaluation

  • Basics of deep learning

• Hands-on experience with NumPy, Pandas, Scikit-learn, and TensorFlow or PyTorch.

• Practical experience working on AI/ML projects.

• Prior experience in teaching, mentoring, training, or technical support.

• Strong Odia communication skills with the ability to explain technical concepts clearly.

Good to Have

• Experience with ML model deployment or production workflows.

• Familiarity with MLOps and Docker.

• Experience with NLP or Computer Vision projects.

• Familiarity with Git, Jupyter, and cloud platforms.

• Experience conducting technical interviews or assessments.

• Experience reviewing ML projects, portfolios, or resumes.

• Experience mentoring students, developers, or early-career professionals.

Why Join Us?

• Make a direct impact on learners building careers in AI and Machine Learning.

• Help learners build practical, industry-relevant AI/ML projects.

• Work remotely with a flexible 6–8 hours per week commitment.

• Collaborate with Masai School and a premier academic institution.

• Share your industry experience while developing your teaching and mentoring skills.

• Stay connected with evolving AI/ML technologies and industry practices.