Available for full-time roles, June 2026

Prasanna
Patil

Backend Developer · Pune, Maharashtra, India

I build backend systems in Python. Right now that means CCTV feeds, object tracking, and a lot of Python at Zuneko Labs.

scroll

intro

About

  • Based inPune, Maharashtra, India
  • CurrentlyComputer Vision Intern @ Zuneko Labs
  • Graduating2026
  • FocusBackend + AI systems
  • AvailableFull-time from June 2026

I write Python for a living — APIs, async workers, database design, and wiring LLMs into things that actually work in production. Right now I'm at Zuneko Labs building a computer vision pipeline for CCTV feeds. Before that, six months at Shivohini TechAI building WhatsApp automation and LLM-backed agents for real businesses.

stack

Technical Stack

daily

What I reach for without thinking.

Python, FastAPI, Pydantic, SQLAlchemy, PostgreSQL, Redis, Celery, Docker, Git/GitHub, Linux/Bash, Postman, pytest. This is the stack I'd use to start something new tomorrow — REST APIs, async workers, schema migrations, the works.

production

Shipped at scale.

Django, Flask, MongoDB, Supabase, OpenCV, YOLO, DeepSORT, TensorFlow, PyTorch, CNN/LSTM, Librosa, PyAudio, LLM APIs (OpenAI + LLaMA), Meta WhatsApp Business API, Twilio, Webhooks, Nginx, GitHub Actions. Used across internships on real workloads — 93.27% accuracy on SER, live multi-stream CCTV pipelines, WhatsApp automation handling business traffic.

learning

Currently picking up.

Vector databases (Qdrant, Pinecone), MLOps tooling (MLflow, DVC), gRPC, WebSockets, Kubernetes basics, AWS (Lambda, S3, EC2), Rust for systems work. I prefer FastAPI over Django when I'm building something new — Django is great but it fights you when you want to move fast.

work

Selected Work

// 01

Speech Sentiment Analysis (SER)

Speech Emotion Recognition system using CNN, LSTM, and CLSTM. Trained on CREMA-D, RAVDESS, TESS, and SAVEE — 93.27% accuracy. Real-time inference pipeline for live audio, built for customer service and healthcare use cases.

PythonTensorFlowCNNLSTMLibrosa
LIVE
// 02

CCTV Analytics for Crime & Crowd Management

End-to-end surveillance platform for public safety. Crowd density estimation, crime detection, facial recognition. MongoDB for event persistence, Twilio and WhatsApp for real-time alerts. Presented at Smart India Hackathon 2023.

PythonOpenCVDjangoMongoDBTwilio
order confirmed ✓
track shipment →
delivered · 14:32
// 03

WhatsApp Automation & AI Agent Platform

Backend for automated WhatsApp workflows — webhook ingestion, user state tracking, async AI responses, conversation history. Redis + Celery for reliability. Built for a client at Shivohini TechAI.

FastAPIPostgreSQLRedisCeleryMeta API
Private repo

career

Experience

Present

Zuneko Labs by Emdee Digitronics

Computer Vision Intern

  • Built a real-time person detection and tracking pipeline on CCTV feeds. Frame-by-frame detection + multi-frame tracking to keep identity consistent across streams.
  • Built a WhatsApp-based document ingestion system using the WhatsApp Business API — pulls media from group chats, uploads to Google Drive automatically.
  • Wrote a recovery mechanism that backfills missed files after downtime or network failures. No manual intervention needed.
6 mo

Shivohini TechAI LLP

AI/ML Intern (Backend-Focused)

  • Built backend for conversational AI agents using LLaMA and OpenAI APIs. Focused on keeping context across turns without blowing token budgets.
  • Built WhatsApp automation for clients — webhook ingestion, message routing, template management via Meta Business API.
  • Async task execution with Redis and Celery. Message processing, AI inference, and DB writes all off the request thread.
  • Migrated client databases from MySQL to Supabase/PostgreSQL mid-project. Kept the AI agents running throughout.
  • Talked directly to clients to figure out what they actually needed, not just what they asked for.

Smart India Hackathon (Government of India)

Finalist — Backend & CV

  • Built a CCTV analytics backend for crime detection and crowd monitoring. Presented to a government panel.
  • CV pipeline in OpenCV: facial recognition, crowd counting, anomaly detection.
  • APIs + background workers for real-time video analysis and alert dispatch.
  • Twilio and WhatsApp integration for instant incident notifications.

background

Education

2022 – 2026

B.Tech in Artificial Intelligence & Data Science

Dr. D. Y. Patil School of Science & Technology, Pune

credentials

Certifications

2025

Oracle Cloud Infrastructure 2025 Certified Generative AI Professional

Oracle University

2024

Machine Learning & Data Science Using Python

Infosys Springboard

2024

IgniteX Program Participant

Wadhwani Foundation

2023

Smart India Hackathon Finalist

Government of India

get in touch

Contact

Looking for full-time roles
starting June 2026.

If you're building something interesting, email me. I reply within a day.

Location

Pune, Maharashtra, India