AI / ML Engineer

Div Agarwal

Building AI systems at the intersection of research and product. NYU CS · Full-stack execution.

I build AI systems that have to survive both research constraints and production reality: retrieval pipelines, ML workflows, and full-stack interfaces that move from prototype to shipped product. My work spans applied research at NYU's Neuroinformatics Lab — building event-detection models (0.92 F1) and a browser tool used by neuroscientists — and engineering worked at AdsGency AI, where I built natural language querying systems over multi-source data.

I care about the gap between a model that works in a notebook and a system that holds up when real users touch it. Most of my projects live in that gap: local RAG systems with modular retrieval, serverless automation pipelines, and full-stack products with real interfaces on top of AI.

Previously: Software Engineer at AdsGency AI (San Francisco). Researcher at NYU Neuroinformatics Lab.

Experience

Software Engineer—AdsGency AIFeb 2026 – March 2026 · San Francisco, CA
  • •Built a natural language querying system generating SQL via DuckDB across multiple data sources.
  • •Developed a ranking and scoring system optimizing data selection for audio, image, and video ad generation.
Researcher—NYU Neuroinformatics LabOct 2024 – Feb 2026 · New York, NY
  • •Trained ML/DL models for neural event detection — achieving 0.92 F1 on voltage imaging data.
  • •Built a browser-based tool for interactive exploration of calcium trace data used by the lab team.
Data Analyst—AdeptmindFeb 2023 – Jul 2023 · Toronto, Canada
  • •Scaled landing pages from 10K to 80K, driving a 20% monthly traffic increase via LLM-generated content and SEO.
  • •Built a Streamlit dashboard for monitoring performance across 19 clients.
Research Engineer—EnordNov 2022 – Feb 2023 · New Delhi, India
  • •Worked on state of the art depth estimation models using Deep Learning for Autonomous Drone Navigation with ROS and Nvidia systems.
Head of Autonomous Department—Team OJAS (Formula Student)Sep 2020 – Feb 2022 · VIT Vellore, India
  • •Led team to become the first Indian qualifiers for Formula Student Hungary.
  • •Implemented YOLO-based detection achieving 92% accuracy; managed perception, planning, and control tracks.

Skills

Core: Python, PyTorch, SQL, React / Next.js, AWS, Docker, Git

Also: HuggingFace, LlamaIndex, RAG, LangGraph, FastAPI, TensorFlow, Pandas, NumPy, Solidity, ROS, MATLAB

Personal

Outside of work I take long walks, attend orchestral concerts, and cook. I'm drawn to classic fiction and philosophical books. My music taste runs from Dire Straits and Pink Floyd to Steven Wilson and Pearl Jam.