AI Engineer · New Delhi, India

I Build AI Systems That Ship to Production

>building

3 systems in production/New Delhi/open to work

  • Techolution
  • ·12pt BLEU ↑
  • ·50% accuracy ↑
  • ·900+ problems
Jatin Singh — AI Engineer
// jatin_singh.jpg · AI Engineerlive
By the Numbers

Outcomes, Not Buzzwords

Every number here came from a system running in production.

M01live
0%

Whisper accuracy improvement

M02live
0pt

BLEU score increase

M03live
0%

Faster model retraining

M04live
0+

Problems solved

M05live
0+

Production models fine-tuned

M06live
0+

ML strategies backtested

The Arc

From Contests to Production

Competitive Programmer → ML Intern → Cybersecurity AI → Translation Systems → Custom Agent Builder.

#0001
The Foundation
2021 — PresentCompetitive Programmer@ Codeforces · LeetCode · CodeChef

900+ problems solved. Codeforces Specialist (1494), LeetCode top 2% (2112). Led 35+ members as CodeChef Chapter Technical Lead.

#0002
First Production AI
2023ML Intern → Cybersecurity AI@ Culinda

Built a Cybersecurity RAG chatbot that drove a 30% improvement in issue resolution, plus an NLP-to-SQL Electron app on a fine-tuned model.

#0003
Translation Systems
Aug 2024 — PresentAI Engineer@ Techolution

Fusion-RAG English-to-Dutch translation with a custom glossary and MLOps retraining loop — a 12-point BLEU increase and 30% accuracy gain.

#0004
Speech & Scale
2024 — PresentAI Engineer@ Techolution

Fine-tuned Whisper with custom vocabulary for a 50% accuracy improvement on Indian-origin words, served through a 30%-faster Airflow/MLflow CI-CD pipeline.

#0005
Custom Agent Builder
PresentAI Engineer@ Techolution

Architected a centralized RLEF assistant with custom agents and tools built from scratch — no external frameworks, full control over the loop.

// I never ship code I wouldn't run in production.

The Ecosystem

How the Pieces Connect

Not a badge wall — a stack where skills feed into each other. FastAPI → Docker → AWS is one path; the model layer rides on top.

AI / ML

The core — language, vision, and learning systems.

· LLMs· RAG· Fusion RAG· AI Agents· Fine-Tuning (Whisper, translation)· Prompt Engineering· Sentiment Analysis· Computer Vision· CNN

Backend

APIs and data stores that hold up under load.

· Python· FastAPI· Flask· Node.js· Express· REST APIs· PostgreSQL· MongoDB· Redis

MLOps

Ship, monitor, retrain — the production loop.

· MLflow· Airflow· ZenML· DagsHub· Mage· AWS EC2· GCP· Docker· CI/CD Pipelines

Frontend

Interfaces for the systems I build.

· React· Next.js· TailwindCSS· JavaScript· HTML/CSS

Languages

Fundamentals, sharpened by competitive programming.

· Python· C / C++· JavaScript· DSA
Deploy chain
FastAPI
Docker
AWS
Selected Work

Systems That Shipped

Eight real projects across AI/ML, MLOps, and full-stack — each with the problem it solved.

PRJ-01status: shipped
AI/MLTecholution

Production translation that actually respects domain terminology.

English-to-Dutch Translation System

problem

Generic translation models mangled domain-specific glossary terms and drifted over time.

solution

Built a Fusion-RAG pipeline with a custom glossary and a continuous MLOps retraining loop to keep quality climbing.

12pt BLEU increase · 30% accuracy gain

LLMs · Fusion RAG · Fine-Tuning · MLflow · Airflow

LLMs → Fusion RAG → Fine-Tuning → MLflow → Airflow
PRJ-02status: shipped
AI/MLTecholution

Transcription that finally gets Indian-origin words right.

Whisper Fine-Tuning System

problem

Off-the-shelf Whisper mis-transcribed Indian names and domain vocabulary, breaking downstream NLP.

solution

Fine-tuned Whisper with a custom vocabulary and curated audio set, then served it behind a fast inference path.

50% accuracy improvement

Whisper · Fine-Tuning · Python · PyTorch

Whisper → Fine-Tuning → Python → PyTorch
PRJ-03status: shipped
AI/MLTecholution

An agent platform with no framework lock-in — full control of the loop.

Centralized RLEF Assistant

problem

Off-the-shelf agent frameworks hid the control flow and made debugging production behavior painful.

solution

Built custom agents and tools from scratch — orchestration, tool-calling, and reinforcement-from-feedback loop, all owned in-house.

Zero external agent frameworks

AI Agents · LLMs · Python · FastAPI

AI Agents → LLMs → Python → FastAPI
PRJ-04status: shipped
AI/MLCulinda

Turned a sprawling security knowledge base into instant answers.

Cybersecurity RAG Chatbot

problem

Security teams burned hours hunting through scattered documentation to resolve recurring issues.

solution

Built an NLP + LLM RAG chatbot grounded in the internal knowledge base with citation-backed responses.

30% issue-resolution improvement

RAG · NLP · LLMs · Vector DB

RAG → NLP → LLMs → Vector DB
PRJ-05status: shipped
Full-StackCulinda

Let non-technical users query data in plain English.

NLP-to-SQL Electron App

problem

Analysts needed SQL fluency to explore data and build visualizations — a hard bottleneck.

solution

Shipped a desktop Electron app on a fine-tuned NLP-to-SQL model with natural-language-editable data visualizations.

NLP-to-SQL · Fine-Tuning · Electron · React

NLP-to-SQL → Fine-Tuning → Electron → React
PRJ-06status: shipped
MLOps

Model retraining that runs itself, end to end.

Automated CI-CD ML Pipeline

problem

Manual retraining and deployment slowed iteration and invited human error.

solution

Built an Airflow + MLflow pipeline on AWS EC2 for a Medical MNIST classifier — automated training, tracking, and deployment.

30% faster model retraining

Airflow · MLflow · AWS EC2 · Docker · CI/CD

Airflow → MLflow → AWS EC2 → Docker → CI/CD
PRJ-07status: shipped
AI/MLVzya

A research bench for ML-driven trading ideas.

AI Trading Strategy Platform

problem

Trading hypotheses needed rigorous, repeatable backtesting before any capital was at risk.

solution

Researched, implemented, and backtested 15+ ML trading strategies with a unified evaluation harness.

15+ strategies backtested

Python · ML · Backtesting · Pandas

Python → ML → Backtesting → Pandas
PRJ-08status: shipped
AI/ML

Wearable assistance, controlled entirely by voice.

AI Glasses for Visually Impaired

problem

Visually impaired users needed hands-free, real-time help understanding their surroundings.

solution

Built smart glasses with speech recognition driving 4+ voice-controlled functionalities for daily assistance.

4+ voice-controlled functions

Speech Recognition · Computer Vision · Python · Embedded

Speech Recognition → Computer Vision → Python → Embedded
principles

How I Build

Four ideas that decide what I ship and how.

P1

Consistency

900+ problems solved, one at a time.

P2

Precision

I never ship code I wouldn't run in production.

P3

Mastery

Deep expertise over broad mediocrity.

P4

Resilience

Every debug session is a lesson.

status: open to opportunities

Full-Time AI Engineering · Remote Roles · Freelance AI Projects · Consulting

// Typically responds within 24 hours

Get in Touch

Let's Build Something Extraordinary

Full-time role or freelance project — tell me what you're after and I'll get back within 24 hours.

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