AI/ML Engineer · creator of OlaiEdge, HERM4AI and TAEL-Agent · building applied AI that holds up under real-world constraints, on devices never meant to run AI.
📍 Hyderabad, India | 🟢 Open to AI/ML and software engineering roles
- 💼 Role: AI/ML Engineer specializing in Generative AI, Agentic AI, LLM fine-tuning, agent memory, Computer Vision, and edge/local LLM inference.
- 🔬 Focus: Local-first, privacy-preserving AI: fine-tuning small models (QLoRA), serving them as GGUF on CPU-only hardware, and wrapping them in reliable agent runtimes (tool calling, persistent memory, context management).
- 🎓 Education: B.Tech in CSE (AI & ML), Vignan Institute of Technology and Science, Hyderabad (2022–2026).
- 👀 Interests: Applied AI, Agentic AI, Local LLMs, NLP, Computer Vision, MLOps.
| Project | What it is | Stack |
|---|---|---|
| ⚡ OlaiEdge (formerly FastAgent · Open Source, MIT) | Headless, drop-in local LLM runtime (SDK + background daemon) for desktop apps. Cuts steady-state prompt latency from ~3,500 ms to ~73 ms on a CPU-only, 8 GB machine with zero OOM failures in long tool loops. Adds a RAM-budget enforcer, process watchdog, multi-tab slot cache, and offline signed licensing; 26 tests. Paper | Python, llama.cpp, LCP slot caching, 8-bit KV-cache quantization, GBNF, Electron/Tauri/Flutter SDKs |
| 🧠 HERM4AI (Open Source, MIT) | Human-like Evolving & Reasoning Memory for AI: a model-free cognitive memory architecture for LLM agents (valid-time store, 7-slot working memory, associative knowledge graph, sleep-phase consolidation, ACT-R arbitration, Q-MIA provenance). Shows flat vector RAG suffers temporal inversion (41.7% obsolete retrievals), dual collapse (9.0% top-1 at 10k passages), and prompt poisoning (33–40% hallucination); HERM4AI reaches 100% on 7 benchmark suites at <2 ms CPU latency; 36 tests. Paper | Python, SQLite, Knowledge Graphs, ACT-R |
| 🛠️ TAEL-Agent · 🤗 Model | Privacy-preserving local autonomous SWE agent. IBM Granite 3.1 2B Instruct fine-tuned with QLoRA on a 29,900-sample, three-phase curriculum, deployed as a 4-bit GGUF. Runtime has 9-category task routing, 10 sandboxed workspace tools, four-pillar persistent memory, and context-budget management. VS Code extension with refactoring, diff previews, and autonomous tool execution. 8/8 benchmark-domain passes in the reported evaluation suite. | QLoRA, GGUF, Ollama, TypeScript, VS Code API |
| 🐾 WildGuardAI (IEEE Xplore, 2026) | Real-time wildlife-conflict prediction from camera feeds with GPS-based alerts for forest officers and villagers. | YOLOv12n, BoT-SORT, Kalman Filter, Flask, SQLite |
| 🧓 JivanMitra | Offline-first, voice-enabled, multilingual AI companion for elders in India. | LangChain, RAG, agentic AI |
More projects:
- 🌍 Terrascope AI (live): zero-paid-API platform scoring any city or coordinate across 16 socio-environmental dimensions and 5 personas, using rule-based scoring over Open-Meteo, OpenStreetMap Overpass, and Wikipedia data. Deployed on Cloudflare Pages.
- 🔒 Personal AI Agent: local-first, privacy-focused assistant (Ollama, LanceDB).
- 📚 Offline Deep Research Agent: reasons over documents entirely offline (Ollama, Mistral, LangChain).
- 🧑💼 TalentRank AI (live demo): AI-assisted recruiting platform with JWT auth, AI candidate ranking, and analytics (React 18, Vite, Express, SQLite).
- 🪶 Hearthwren (in development): local-first, CPU-only AI coding agent.
Full list in the portfolio archive.
- HERM4AI: Human-like Evolving & Reasoning Memory for Artificial Intelligence — Zenodo, 2026 · Read the paper
- Hardware-Adaptive Inference Orchestration: Zero-Overhead Local LLM Agents on Resource-Constrained Edge Devices (OlaiEdge) — Zenodo, 2026 · Read the paper
- Wild Guard AI: Real-Time Wildlife Conflict Prediction — IEEE Xplore, ICICI 2026 · View on IEEE Xplore
- OlaiEdge, HERM4AI and TAEL-Agent: Creator and maintainer.
- sklearn-genetic-opt: Contributor. Documented parallel processing with
n_jobsinGASearchCV(PR #178 merged, resolving Issue #152).
| Area | Tools |
|---|---|
| Languages | Python, TypeScript, JavaScript, Java, C, C++, SQL |
| AI/ML & Vision | LLMs, Agentic AI, LLM Fine-Tuning (QLoRA/LoRA), RAG, NLP, Computer Vision, scikit-learn, TensorFlow, YOLOv12n, BoT-SORT, Kalman Filter, Vector Embeddings, Knowledge Graphs |
| LLM & Agent Systems | Ollama, llama.cpp, GGUF, KV-Cache Quantization, Prompt Caching, Grammar-Constrained Decoding (GBNF), Tool Calling, Persistent Agent Memory, ReAct |
| Frameworks & Tools | FastAPI, Flask, LangChain, LangGraph, React, Node.js, Streamlit, LanceDB, ChromaDB, SQLite, Hugging Face, Git/GitHub, VS Code Extension Development, REST APIs |
- Oracle Certified Foundations Associate: Agentic AI
- Deep Research with LangGraph (LangChain Academy)
- Hugging Face Agents Course
- Databricks Fundamentals (Databricks Academy)
- TCS iON NQT (IT): Qualified
Open to AI/ML engineering and software roles: LinkedIn · Email · Portfolio
I enjoy turning complex AI ideas into simple, usable systems, especially for people in low-resource settings and for devices that were never meant to run AI.