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Tarun Jain

@tarunjain1

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ML engineer at Wanderlust who engineered Ark, processing 100k+ documents for 10+ enterprise clients.

India

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At Wanderlust, I engineered Ark, a cloud-agnostic ETL pipeline that converted complex, unstructured documents into structured data. It processed over 100k documents and was used by 10+ enterprise clients.

I also built a RAG pipeline for LLM-based document querying and automated P&ID diagram analysis for CHIYODA and NISSIN, cutting processing time by about 50%. At DroneArch Systems and Technologies, I developed aerial crowd-counting and fire-detection models and deployed deep learning pipelines on Google Cloud Platform and Firebase.

In my projects, I reduced real-time bidding inference from 30 ms to 3 ms and built MediLink, an AI health kiosk with online and offline assessments. I also developed HateShield, a Chrome extension for real-time toxic-comment classification.

Experience

Work history, roles, and key accomplishments

ML Engineer

Wanderlust

Mar 2025 - Mar 2026 (1 year)

Engineered a cloud-agnostic ETL pipeline for processing over 100k unstructured documents, and built a RAG pipeline for LLM-based document querying. Automated P&ID diagram analysis for CHIYODA and NISSIN, cutting processing time by ~50%.

ETL RAG LLM Computer Vision Cloud Computing Document Processing

AI Engineer Intern

DroneArch Systems and Technologies

Sep 2024 - Nov 2024 (2 months)

Led development of crowd-counting and fire-detection models using YOLO, R-CNN, and SASNet-inspired architecture, achieving ~70% detection confidence on aerial imagery. Deployed deep learning pipelines on Google Cloud Platform and Firebase for real-time aerial analytics.

YOLO R CNN SASNet Deep Learning Google Cloud Platform Firebase

Education

Degrees, certifications, and relevant coursework

Delhi Technological University

B.Tech, Computer Science Engineering

2023 -

Grade: 8.729

Pursuing a Bachelor of Technology in Computer Science Engineering with a current CGPA of 8.729.

Universal Public School

CBSE (Class XII), General Studies

Grade: 95%

Completed Class XII under the CBSE board with 95%.

Universal Public School

CBSE (Class X), General Studies

Grade: 94.1%

Completed Class X under the CBSE board with 94.1%.

Stanford University

ML Specialization, Machine Learning

Completed the Machine Learning Specialization, covering neural networks, deep learning, CNN, structuring ML projects, regularization, and optimization.