
"AI/ML Engineer | Diffusion Models | Web3/Blockchain | GPU Computing" https://rahulkhunte.github.io/portfolio/
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Assessing your cultural and operational fit
rahulk-ddpm
March 22, 2026 – Present
DDPM → VideoDiT built from scratch in PyTorch — image diffusion, spatiotemporal video generation from pure noise, and a correctness-guaranteed pedagogy engine. No pretrained weights, no diffusers.
View Projectflasharb-base
March 10, 2026 – Present
⚡ Live flash loan arbitrage bot on Base mainnet — Uniswap V3 vs Aerodrome, 34 routes, 200ms scan speed
View ProjectPDF-RAG-Chatbot
February 5, 2026 – Present
Production document Q&A using RAG, Llama 3.1, and L40 GPU
View ProjectDAMN-prototype
January 11, 2026 – Present
Decentralized AI Memory Network (DAMN) — a persistent learning and memory-sharing infrastructure for autonomous agents. Blockchain + IPFS-based memory layer enabling cross-agent experience reuse and scalable distributed intelligence.
View ProjectCultural Fit Analysis
The candidate's portfolio shows a strong inclination towards cutting-edge technologies (blockchain, advanced AI models) and independent project development. This suggests a fit for innovative, research-oriented, and self-driven environments. The diversity of projects, from AI to blockchain and arbitrage bots, indicates a broad technical curiosity and adaptability, which can be a positive cultural fit for dynamic teams.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest a self-starter with a strong drive for complex technical challenges.