About KGP Talkie:
KGP Talkie is a code-first AI education brand trusted by 200,000+ learners worldwide. We teach Python, Machine Learning, Deep Learning, NLP, and Generative AI through practical, production-focused tutorials, real projects, and full walkthroughs on RAG systems, AI agents, LangChain, and LangGraph. Free tutorials on YouTube, professional courses on Udemy (4.8★), and structured learning paths. Founded by Laxmi Kant Tiwari, an IIT Kharagpur alumnus who left a six-figure job to teach AI full time.
Every video watched, every tutorial finished, every question asked in the comments is data. We want someone to help us read it, and turn it into better teaching.
What you'll actually do:
- Pull and clean data from YouTube analytics, Udemy, our website, and learner questions into workable datasets.
- Run exploratory analysis and build simple dashboards to track engagement, completion, and drop-offs.
- Do NLP on learner comments and questions to surface content gaps and points of confusion.
- Run small experiments on titles, thumbnails, and tutorial structure, and measure real learning impact.
- Prototype with the AI we teach, helping build things like a RAG-based tutor bot over our tutorial library using LangChain and real LLMs.
Who we're looking for:
Before applying, we recommend taking a little time to understand KGP Talkie, the type of content we create, and the learners we serve. You may explore our website, YouTube tutorials, or LinkedIn content to get a sense of our work and teaching approach. Candidates who are familiar with our niche, audience, and content style are usually better able to understand the role and have more meaningful interview discussions.
Core skills:
- Strong Python (Pandas, NumPy) and classical ML with Scikit-Learn, with the ability to frame a problem, train a baseline, and evaluate it properly.
- Hands-on experience with PyTorch (preferred), including at least one model you've built and trained yourself.
- SQL for pulling and joining data independently.
- Solid statistics, including distributions, hypothesis testing, and A/B test design.
- EDA that tells a story with Matplotlib, Seaborn, or Plotly, along with comfort in Jupyter/Colab and Git.
A genuine plus:
- Exposure to LLMs, RAG, embeddings, or vector stores.
- Hands-on with LangChain or LangGraph.
- A public GitHub, Kaggle, or Colab project you can walk us through.
Pay: From ₹400,000.00 per year
Benefits:
Work Location: Remote
