Data Science Trainer

Larsen & Toubro - EduTech (L&T); Mumbai; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Larsen & Toubro - EduTech invites applications for a role designing and developing AI/ML curriculum and learning paths. You will create engaging materials, mentor students through labs, capstones and hackathons, and deliver instructor-led sessions both in classroom and virtual formats.

You will also develop assessments, coding challenges, and rubrics, review content for alignment with industry trends, and collaborate with academic partners to improve learner outcomes.

Qualifications

• Design and develop industry-aligned curriculum and learning paths in AI/ML.

Responsibilities

• Design and develop industry-aligned curriculum and learning paths in AI/ML.

Skills

Python

Data Structures

Pandas/NumPy

Data Preprocessing

ML Algorithms

Model Evaluation

Deep Learning

TensorFlow/PyTorch

Computer Vision

NLP

SQL

Power BI/Tableau

Prompt Engineering

LMS Experience

GitHub

REST APIs

Cloud Platforms

Jupyter Notebook

Streamlit/Gradio

Docker

Education

Bachelor's or Master's in CS/IT/AI/Data Science

Tools

TensorFlow or PyTorch

Jupyter Notebook

Docker

Flask/FastAPI

Power BI/Tableau

GitHub

REST APIs

Cloud Platforms (Azure/AWS/GCP)

Streamlit/Gradio

Job description

Key Responsibilities

• Design and develop industry-aligned curriculum and learning paths in AI/ML.
• Create engaging training materials, including presentations, lab manuals, coding exercises, case studies, assignments, and projects.
• Deliver instructor-led classroom and virtual training sessions.
• Mentor students during hands-on labs, capstone projects, and hackathons.
• Develop practical assessments, coding challenges, and evaluation rubrics.
• Review and continuously enhance existing learning content based on industry trends.
• Collaborate with instructional designers and academic partners to improve learner outcomes.
• Provide technical guidance to trainers and support faculty enablement programs.
• Stay updated with emerging AI/ML technologies and integrate them into the curriculum.

Required Technical Skills

Mathematics & Statistics for Machine Learning

• Statistics and Probability
• Linear Algebra
• Basic Calculus (Differentiation, Optimization)

Programming & Problem Solving

• Core Python Programming Concepts
• Data Structures and Algorithmic Problem Solving
• Pandas and NumPy for Data Manipulation
• Data Preprocessing and Feature Engineering

Machine Learning

• Supervised and Unsupervised Learning Algorithms
• Model Evaluation Metrics (Accuracy, Precision/Recall, F1, ROC-AUC, RMSE, etc.)
• Scikit-learn
• Bias-Variance Tradeoff, Overfitting/Underfitting, Regularization

Deep Learning

• Deep Learning Fundamentals
• CNNs, RNNs/LSTMs, Transfer Learning Models, VAE, and GAN
• Computer Vision and NLP concepts
• TensorFlow or PyTorch (at least one)

Data Analytics & Visualization

• Advanced Excel for Data Analysis
• Power BI Fundamentals, Tableau, Dashboard Development, and Data Storytelling

Database

• SQL Fundamentals and Database Querying (Joins, Aggregations, Subqueries)

Generative AI & Agentic AI

• Basics of Generative AI (GenAI)
• LLM Transformer Architecture and Working Principles
• RAG, Prompt Engineering and Fine-tuning techniques
• Agentic AI Concepts and Multi-Agent Systems

Preferred Skills

• Git and GitHub
• REST APIs (Flask or Fast API)
• Cloud platforms (Azure, AWS, or GCP) - especially AI/ML services
• MLOps Basics (model deployment, versioning, monitoring)
• Jupyter Notebook
• Streamlit or Gradio
• Docker

Educational Qualification

• Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
• Candidates with a Bachelor of Engineering (B.E./B.Tech.), Master of Engineering (M.E./M.Tech.), MCA, or equivalent qualifications are encouraged to apply.

Required Competencies:

• Excellent communication and presentation skills.
• Strong analytical and problem-solving abilities.
• Passion for teaching and mentoring.
• Ability to simplify complex mathematical and technical concepts.
• Strong curriculum development and documentation skills.
• Effective stakeholder management and collaboration.
• Time management and multitasking abilities.

Preferred Experience:

• Experience creating project-based learning content and coding assessments.
• Hands-on industry experience as a Data Scientist, ML Engineer, or AI Engineer.
• Experience with Learning Management Systems (LMS) is an added advantage.

Key Deliverables

• Curriculum and syllabus design for Lab programs
• Instructor presentations
• Lab manuals and coding exercises
• Assignments and assessments
• Capstone projects
• Question banks and evaluation rubrics
• Faculty enablement sessions