Open to remote AI/ML & full-stack internships

Atanu Adhikari

I build AI agents, RAG pipelines, ML models and MERN web apps.

AI/ML & Full-Stack Developer. I build AI agents (LangGraph, RAG, LLMs), ML models in Python, and MERN web apps.

B.Tech CS & AI @ Newton School of Technology · Greater Kolkata Area, India

01about

Player bio

I'm a third-year B.Tech student in Computer Science & AI at Newton School of Technology, based in the Greater Kolkata Area. I learn by shipping real projects: AI agents built with LangGraph and LLMs, machine-learning models in Python, and MERN web apps deployed on Vercel and Render.

I'm most interested in AI agents and applied ML, and I'm comfortable across the stack, from a FastAPI or Express backend to a React front end. Right now I'm looking for remote AI/ML or full-stack internships.

Class
AI/ML & Full-Stack Developer
Guild
B.Tech CS & AI, Newton School of Technology
Region
Greater Kolkata Area, India
Main quest
AI agents & applied ML
Status
Open to remote internships
Local time

02skills

Skill loadout

AI / ML

  • Python
  • NumPy
  • Pandas
  • scikit-learn
  • XGBoost
  • LangChain
  • LangGraph
  • LLMs (Llama 3.1 via Groq)
  • RAG
  • librosa (audio features)
  • Jupyter / Colab

Backend

  • FastAPI
  • Flask
  • Node.js
  • Express.js
  • REST APIs
  • JWT auth
  • MongoDB

Frontend

  • React
  • React Router
  • JavaScript
  • HTML / CSS
  • Streamlit

Deploy / Tools

  • Git / GitHub
  • Vercel
  • Render
  • nginx
  • DNS / HTTPS

Data & BI

  • Tableau

DSA

  • NeetCode / LeetCode in Python

03projects

Quest log

AI / ML

AI agent

Shipped

Student GitHub Reviewer

An AI agent that reviews a student's GitHub portfolio. A LangGraph pipeline drives Llama 3.1 (via Groq), served by a FastAPI backend on Render with a Streamlit UI.

  • LangGraph
  • Llama 3.1
  • Groq
  • FastAPI
  • Streamlit
  • Render

Audio ML · classification

Shipped

Infant State Recognition from Cry Audio

Classifies infant cry audio into 8 need states: hungry, tired, belly pain, burping, scared, lonely, discomfort and cold/hot. 511 cleaned clips become a 218-dim librosa feature vector (MFCC, delta-MFCC, log-mel, chroma, spectral contrast, tonnetz, ZCR, RMS) fed to a cost-sensitive Random Forest (300 trees, balanced class weights, 5-fold stratified CV).

Test accuracy
81.6%
Macro F1
32.0%

Honest read: the dataset is heavily imbalanced (~75% "hungry"), so accuracy flatters the model. Macro F1 is the metric I'm working to improve. Next: data augmentation and a CNN on log-mel spectrograms.

  • Python
  • librosa
  • scikit-learn
  • Random Forest
  • NumPy
  • Pandas

ML · course project

Shipped

Flight Delay Risk Prediction

Predicts, the night before departure, whether a New York flight will arrive 15+ minutes late, using 336,776 departures from 2013 (nycflights13). Past-only features with a leakage test, a chronological train/validation/test split, logistic regression vs XGBoost, Platt calibration with rolling recalibration, and a what-if rescheduling analysis.

PR-AUC (XGBoost)
0.468
Prior baseline
0.335

Honest read: December test set. Rolling recalibration cut calibration error (ECE) from 0.102 to 0.047, but at precision ≥ 0.5 recall is only 0.035. There's no weather data, which limits day-ahead accuracy.

  • Python
  • XGBoost
  • scikit-learn
  • Pandas
  • Jupyter

Full-stack

React · e-commerce

Shipped

QuickCart

A React e-commerce cart: products fetched from MockAPI, add-to-cart from product cards, quantity controls (1–10), real-time totals and a simulated checkout flow. Multi-page navigation with React Router, responsive on mobile, tablet and desktop. Deployed on Vercel.

  • React
  • React Router
  • JavaScript
  • MockAPI
  • Vercel

Personal finance · in progress

In progress

Spendly

An expense tracker built step by step with Claude Code. The Flask app has its landing, register and login pages in place; authentication, profile and add/edit/delete expenses are the next steps.

  • Python
  • Flask
  • pytest
  • Claude Code

Other work

04experience & education

The journey so far

Every level is a real milestone. Scroll to play through it.

  1. LVL 01Cleared

    Spawn point: B.Tech, Computer Science & AI

    Newton School of Technology · – · currently in 3rd year

    Started the degree and began practising DSA in Python with NeetCode and LeetCode.

    • Python
    • DSA
    • Git / GitHub
  2. LVL 02Cleared

    Frontend unlocked: QuickCart

    Built a React e-commerce cart with live pricing, quantity controls and a simulated checkout, and deployed it on Vercel.

    • React
    • React Router
    • Vercel
  3. LVL 03 – PresentCleared

    Full-Stack Developer (Project-Based)

    Self-Directed Projects · Remote

    • Built MediTrack, a MERN health-record manager with JWT auth and role-based access.
    • Co-built Cognify at Construct Hackathon and launched it on Product Hunt.
    • Built QuickCart, a React e-commerce cart deployed on Vercel.
    • Node.js
    • Express
    • MongoDB
    • JWT
  4. Boss fightCleared

    Construct Hackathon: Cognify

    Co-built an AI career-guidance platform during the hackathon, then launched it on Product Hunt.

    • AI agent
    • React
    • Product Hunt launch
  5. LVL 05Cleared

    AI agents: Student GitHub Reviewer

    A LangGraph pipeline drives Llama 3.1 (via Groq) to review a student's GitHub portfolio, served by FastAPI on Render with a Streamlit UI.

    • LangGraph
    • Groq
    • FastAPI
    • Streamlit
  6. LVL 06Cleared

    Applied ML & data

    Classified infant cry audio with librosa features and a cost-sensitive Random Forest, predicted flight-delay risk with calibrated XGBoost, and built Tableau dashboards for Blinkit and Uber data.

    • scikit-learn
    • XGBoost
    • librosa
    • Tableau
  7. Current levelIn progress

    Next quest: join a team

    Looking for a remote AI/ML or full-stack internship where I can ship real features and learn from experienced engineers.

    Send an invite

05badges

Achievements unlocked

  • Hackathon hero

    Co-built Cognify at Construct Hackathon.

  • Launch day

    Launched Cognify on Product Hunt.

  • Ship it ×3

    Three live deployments: MediTrack, QuickCart and Cognify.

  • Agent builder

    A LangGraph agent driving Llama 3.1 via Groq.

  • Full stack

    MERN app with JWT auth and role-based access.

  • Honest metrics

    Reports macro F1 and calibration, not just accuracy.

  • Network engineer

    Private DNS → nginx HTTPS → load-balanced backends.

  • Grinder

    NeetCode / LeetCode solutions in Python.

  • First internship

    Locked. Your team could unlock it.

06contact

Player 2, press start

Let's talk. I'm open to remote AI/ML and full-stack internships. Email is the fastest way to reach me.