Visiting Faculty / Instructor – Classical Machine Learning

AlgoTutor is a leading EdTech company committed to making quality tech education affordable, practical, and accessible. We partner with colleges, universities, and institutions to deliver tailored on-campus and online upskilling programs that align with academic schedules and prepare students for the industry. We are currently seeking

passionate industry professionals who would like to contribute to student development as Visiting Faculty / Part-Time Instructors for our DevOps & Cloud Training Program conducted for students at our partner colleges.

Work Location & Duration:

• College Campus, Electronic City, Bengaluru
• 2-3 Sessions per week
• Program Duration: 6 Weeks
• Session Duration: 2 Hours
• Tentative Start Date : 1st Aug 2026

What You Will Do / Responsibilities Teaching & Delivery

• Deliver instructor-led sessions as part of the Classical Machine Learning curriculum.
• Teach core machine learning concepts with a strong balance of theory, intuition, and hands-on implementation.
• Conduct interactive lectures, including whiteboard explanations, coding walkthroughs, and problem-solving discussions.
• Guide students through practical implementations, labs, assignments, and ML-based case studies.

Topics Covered The course broadly covers foundational concepts in Classical Machine Learning, including supervised learning algorithms, model evaluation, ensemble methods, practical ML workflows, and hands-on implementations using Python-based ML libraries. The curriculum combines theoretical understanding with applied problem-solving and real-world use cases.

Student Engagement & Mentorship

• Support students in developing strong conceptual clarity and practical problem-solving skills in machine learning.
• Provide guidance on assignments, labs, projects, and debugging approaches.
• Address student queries and facilitate technical discussions to deepen learning.
• Mentor students on best practices in experimentation, evaluation, and model interpretation.

Course Delivery Excellence

• Align with the existing curriculum structure, evaluation methods, and academic expectations.
• Collaborate with the academic team to ensure smooth course execution.
• Contribute feedback on curriculum, assignments, and assessment quality.
• Help maintain a high bar for academic rigor and classroom engagement.

Required Qualifications Education

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, AI/ML, Data Science, or a related field.

Experience

• 2–6+ years of relevant experience in Machine Learning, Data Science, AI, Analytics, or related domains (industry or academia).
• Prior teaching, training, mentoring, or technical content delivery experience is strongly preferred.
• Hands-on experience building or deploying machine learning models in real-world scenarios.

Knowledge, Skills, and Abilities

• Strong understanding of core classical machine learning algorithms and statistical learning concepts.
• Good grasp of supervised learning, model evaluation, feature engineering, and ensemble methods.
• Proficiency in Python and familiarity with libraries such as NumPy, Pandas, scikit-learn, Matplotlib, etc.
• Ability to explain complex concepts in a clear, structured, and engaging manner.
• Strong communication, classroom management, and presentation skills.
• High ownership and reliability in a part-time teaching setup.

Application Process Shortlisted candidates will undergo:

• Technical / Knowledge Round – Assessment of ML fundamentals, mathematical intuition, and applied problem solving
• Teaching Round – Demo lecture or topic delivery
• Fitment Round – Alignment with academic expectations and teaching philosophy

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