Open to opportunities

Divyansh Agarwal

@divyanshagarwal1

Full-stack engineer and AI researcher building data-driven products, RAG systems, and computer vision models with measurable impact.

United States

Message

What I'm looking for

I’m looking for a role where I can ship AI-powered products end-to-end—combining full-stack engineering with ML/RAG and computer vision—while running fast experiments, owning performance, and building systems that stay reliable and secure.

I’m a Full Stack Engineer and AI Researcher who turns messy data and complex models into useful, shippable experiences. Most recently, I built an AI-assisted natural language querying system that generated SQL via DuckDB across multiple data sources, plus a ranking/scoring approach to optimize audio, image, and video ad generation workflows.

My research and engineering blend performance, reliability, and experimentation: I achieved a 92% F1 score on detecting fast/slow neural events with LSTM and U-Net (with noise suppression) and deployed an interactive React app on Vercel. I’ve also scaled SEO analytics work (10K→80K landing pages, +20% monthly traffic), built real-time dashboards in Streamlit, and developed lightweight depth estimation models optimized for resource-constrained deployments using PyTorch/CUDA.

Experience

Work history, roles, and key accomplishments

Current

Full Stack Engineer

Current

AdsGency AI

Feb 2026 - Present (3 months)

Built an AI-assisted natural language querying system that generated SQL with DuckDB across multiple data sources, enabling geographic/temporal/category insights. Developed a ranking and scoring system to optimize data selection for audio, image, and video ad generation workflows.

DuckDB SQL Data Integration Ranking Systems Multi Modal Ad Data

AI Researcher

Neuroinformatics Lab, New York University

Oct 2024 - Feb 2026 (1 year 4 months)

Achieved 92% F1 detecting fast/slow neural events using LSTM and U-Net models with noise suppression. Processed large-scale noisy neural data on HPC with Slurm and GPU optimization, validated results via clustering/PCA/embeddings, and deployed an interactive React app on Vercel.

U Net Slurm Embeddings

Data Analyst

Adeptmind

Feb 2023 - Jul 2023 (5 months)

Automated landing page generation to scale from 10K to 80K pages, driving a 20% monthly traffic increase. Created LLM-based SEO content using prompt engineering, built Streamlit dashboards for monitoring/alerts, and produced reports for 19 clients.

Prompt Engineering Streamlit Monitoring Data Visualization

Computer Vision Intern

Enord

Nov 2022 - Feb 2023 (3 months)

Developed lightweight depth estimation models using stereo cameras with PyTorch/CUDA (C++), optimized for real-time deployment on resource-constrained embedded systems like drones. Improved performance robustness for constrained on-device inference.

PyTorch CUDA Real Time AI Inference Computer Vision

Education

Degrees, certifications, and relevant coursework

New York University Tandon School of Engineering

Master of Science, Computer Science

Grade: 3.76/4

Activities and societies: Coursework: Computer Vision, AI for Games, ML, DL, Big Data, Blockchain, Cloud Computing, Information Visualization

Master of Science in Computer Science at NYU Tandon School of Engineering, focusing on coursework including computer vision, machine learning, deep learning, big data, blockchain, cloud computing, and information visualization.

VIT University

Bachelor of Technology, Computer Science and Engineering & Business Systems

Grade: 8.4/10

Activities and societies: Coursework: Computational Statistics, Data Science and Statistical Modeling, Deep Learning, Business, Design Thinking

B.Tech at VIT University in Computer Science and Engineering and Business Systems, covering areas such as computational statistics, data science, deep learning, business, and design thinking.