At Cokonet, we believe learning is not listening—learning is living the experience. We don't do boring 2-hour slide deck lectures or static theoretical teaching.

We are looking for an AI & ML Learning Coach who brings high energy, adaptability, and a growth mindset to the learning space. As a Coach, you won't just teach algorithms—you will facilitate live coding, mentor learners through real-world AI problems, guide portfolio development, and help learners become job-ready AI professionals.

Who You Are (Mindset & Culture Fit)

- A Facilitator, Not a Lecturer: You prefer live coding, interactive challenges, practical projects, and problem-solving over passive slide presentations.
- Obsessed with Growth & Adaptability: You continuously explore new AI frameworks, models, APIs, and AI productivity tools and bring relevant technologies into your workflow.
- Empathetic & Outcome-Driven: You care about learner transformation and helping students build robust portfolios and become interview ready.
- High Energy & Engaging: You can engage learners during classroom sessions, online sprints, bootcamps, workshops, and college hackathons.
- Open to Feedback & Continuous Iteration: You continuously improve curriculum based on AI industry trends, SME inputs, and learner outcomes.

Key Responsibilities1. Facilitate Experiential & Hands-on Learning
- Lead implementation-focused sessions in Python, Data Science, Machine Learning, Deep Learning, and Generative AI.
- Convert complex AI/ML concepts into simple, intuitive, hands-on activities and coding challenges.
- Conduct online and offline training, including evening batches and flexible delivery schedules.
- Create coding exercises, assignments, assessments, practical activities, and AI/ML projects.

1. Coach, Mentor & Build Job-Ready Talent

- Conduct 1-on-1 code reviews, project reviews, portfolio evaluations, and skill-gap analysis.
- Guide learners in building industry-ready AI/ML, Data Science, and Generative AI portfolios.
- Mentor learners on GitHub, Kaggle, project documentation, and deployment.
- Conduct mock technical interviews and provide actionable feedback on technical, communication, and problem-solving skills.

1.



Continuous Curriculum & AI Innovation

- Continuously update learning tracks, datasets, projects, and practical activities based on real-time AI industry requirements.
- Regularly connect with Subject Matter Experts (SMEs) to understand emerging industry expectations.
- Integrate modern AI tools such as ChatGPT, Claude, GitHub Copilot, LangChain, AI APIs, and AI-assisted development tools into the learning workflow.
- Continuously upskill and introduce emerging AI technologies into the classroom.

1. Ecosystem & Industry Engagement

- Represent Cokonet at college campuses through workshops, bootcamps, hackathons, seminars, webinars, and guest sessions.
- Support internship-oriented activities and industry-focused AI/ML projects.
- Collaborate with Academics, Operations, and Placement teams to support learner and hiring outcomes.

Technical Toolkit & Expertise We expect our coaches to be hands-on AI/ML practitioners who can code, build, experiment, and demonstrate real-world AI solutions live in front of an audience.

Core Programming & Data Science

- Python
- NumPy, Pandas
- Matplotlib, Seaborn
- SQL
- Data Cleaning and Exploratory Data Analysis
- Business Statistics and Probability

Machine Learning
- Supervised and Unsupervised Learning
- Regression and Classification
- Clustering
- Feature Engineering
- Model Evaluation and Optimization
- Scikit-learn
- Real-world ML projects and case studies

Deep Learning & AI
- Neural Networks
- Deep Learning concepts
- TensorFlow and/or PyTorch
- NLP fundamentals
- Computer Vision fundamentals
- Model training and evaluation

Generative AI & Modern AI
- Generative AI concepts and applications
- LLMs and Prompt Engineering
- LangChain
- AI APIs
- RAG fundamentals
- Vector databases / embeddings




- AI agents and AI-powered applications
- ChatGPT, Claude, GitHub Copilot, and other modern AI tools

Development & Industry Tools
- Git & GitHub
- Jupyter / Google Colab
- Basic cloud AI/ML awareness
- API integration
- Basic model deployment concepts
- Kaggle and practical AI project development

Academic & Experience Requirements
- Bachelor's/Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Engineering, or a related field.
- 4–6 years of teaching/training experience preferred.
- Experience in a relevant AI/ML, Data Science, or technical domain along with teaching/training experience preferred.
- Preferred: Industry experience with strong training and communication skills.
- Ability to conduct interactive, hands-on, implementation-focused sessions that encourage learner engagement, collaboration, and peer learning rather than lecture-based teaching.
- Strong practical knowledge of AI/ML and the ability to demonstrate concepts through real-world projects.
- Strong communication, presentation, mentoring, and problem-solving skills.
- Passion for teaching, continuous learning, and emerging AI technologies.
- Relevant AI/ML, Data Science, or Generative AI certifications are an added advantage.

Why Join Cokonet?
- Zero Bureaucracy: Freedom to innovate, gamify learning, and experiment with new teaching methods.
- Continuous Up-skilling: Support to learn emerging AI, ML, Generative AI, and advanced frameworks.
- Industry Exposure: Opportunities to interact with SMEs and work on industry-oriented AI projects.
- Impact: Direct ownership in transforming learners into job-ready AI professionals.
- Growth opportunities: Opportunity to grow into senior trainer, academic lead, or learning-content roles.

Pay: ₹50,000.00 - ₹1,700,000.00 per month

Ability to commute/relocate

- Ulloor, Thiruvananthapuram, Kerala: Reliably commute or planning to relocate before starting work (Required)

Experience:
- Teaching / Industry: 4 years (Required)

Language:
- Malayalam (Preferred)
- Fluent English (Required)

Work Location: In person

📌 AI & ML Trainer - Offline (Ulloor)
🏢 Cokonet
📍 Ulloor