📫 adityaaguha@gmail.com | 📞 +91 7304748055
- Job hunting for full-time AI Engineer / Applied AI Developer & Robotics Engineer roles (Pune, Mumbai, Banglore, remote)
Just graduated AI & ML engineer with hands-on research at DRDO on reinforcement learning for quadruped robotics, and a track record of shipping local-first AI systems end to end, agentic assistants, LLM inference servers, and custom benchmarking tools built in C++ and Python. I care about privacy-focused, self-hosted AI infrastructure and getting real performance out of consumer hardware. Outside of core dev work, I run a freelance computer consultancy and create AI/dev-focused content for Instagram and YouTube.
Defence Research and Development Organisation (DRDO), Pune Robotics & Machine Learning Research Intern
Project: Reinforcement Learning Based Quadruped Handstand and Footstand using MuJoCo and JAX
- Developed reinforcement learning control strategies for quadruped robotic balance and posture stabilization
- Worked with the MuJoCo physics simulation environment for robotics modeling
- Implemented and analyzed control policies using JAX-based reinforcement learning, including PPO with curriculum learning
- Contributed to simulation-driven learning and control optimization research
Freelance Computer Consultancy
- Independent consulting on hardware builds, benchmarking, and system setup for individual clients
B.Tech, Computer Science Engineering (AI & ML) Bharati Vidyapeeth Deemed University, DET, Navi Mumbai — CGPA ~8.5, Class of 2026
Local-first ReAct agentic AI assistant. FastAPI backend with SSE streaming, llama.cpp inference (Qwen3-8B), Serper.dev web search, and a Perplexity-style vanilla JS frontend.
Local image generation stack: FastAPI + llama.cpp (Gemma, Metal GPU) + ComfyUI running headless on a MacBook Pro M1 Pro, with one-command install and launch scripts.
Open-source C++ GPU/CPU benchmarking tool for Windows, built and tuned against an RTX 4050.
Companion benchmarking tool for macOS Apple Silicon, using IOKit for GPU detection.
Final-year project: multimodal AI proctoring system combining MediaPipe face/gaze tracking, YOLOv8, and CNN-based audio analysis for exam integrity monitoring. (add repo link)
More Projects
NeuroCourier / GuhaGPT — Multimodal AI agent on Telegram and Discord, Ollama backend, supporting text and image input for privacy-focused interaction. (add repo link)
MeetingMind — Local-first meeting transcription and RAG system: pyannote diarization, faster-whisper, ChromaDB, Ollama, FastAPI + WebSocket. (add repo link)
VisionSense — Real-time scene description combining YOLOv8 object detection with Qwen2.5-VL-3B. (add repo link)
NutriLens — FastAPI + Gemini Vision Telegram bot for food label analysis. (add repo link)
CortexCLI — Textual-based multi-provider chat CLI, with a planned agentic-tool-calling upgrade (GuhaCLI). (add repo link)
n8n Bank Statement Analyser — Local workflow: PDF bank statements parsed and analyzed by AI, results delivered via Telegram, containerized with Docker.
YOLOv8 Vehicle Detection — Custom-trained 6-class vehicle detection model built on a Roboflow dataset. (add repo link)
MiniZIP++ — Custom C++ archiver with a Huffman coding compression layer. (add repo link)
Local LLM Server — FastAPI backend serving locally hosted LLMs via structured APIs, used across several of the projects above. (add repo link)
Encrypted NAS — Fully encrypted, self-hosted network-attached storage with LUKS + Samba, multi-user access across platforms.
TripMind — FastAPI + React + Gemini 2.5 Flash travel planner MVP. (add repo link)
BhashaMitra — Gamified Indian language learning platform, built for a hackathon. (add repo link)
Celestique — Salon platform startup concept.
IVA — Donor-NGO bridge startup concept.
I run and benchmark a small fleet of machines, and treat hardware tuning as seriously as the software on top of it:
- Lenovo LOQ (RTX 4050) — Fedora 44 with a full CUDA + llama.cpp rebuild, ~103 tok/s on Gemma 4 E2B
- MacBook Pro M1 Pro (14", 16GB) — Metal-accelerated inference benchmarking, ComfyUI, PixelStudio Pro host
- ThinkCentre M91p — Repurposed as an OpenMediaVault NAS (Debian 13), SMB shares, CPU-only llama.cpp benchmarking on Sandy Bridge
- ASUS Vivobook OLED 15 (Ryzen 5 7520U) — Cross-platform llama.cpp benchmarking (Vulkan/CPU)
All machines are tied together over Tailscale for remote SSH access, and I regularly run cross-device llama.cpp benchmarks comparing CUDA, Metal, and CPU-only inference paths.
Languages: Python, C++, JavaScript
AI / ML: PyTorch, OpenCV, YOLO, MediaPipe, Reinforcement Learning (PPO, Curriculum RL)
Robotics & Simulation: MuJoCo, JAX, Gymnasium
LLM Infrastructure: llama.cpp, Ollama, ComfyUI, GPU inference (CUDA, Metal, Vulkan), FastAPI, SSE streaming, RAG (ChromaDB)
Computer Vision: YOLOv8, MediaPipe, PaddleOCR, Qwen2.5-VL
Systems: Linux (Fedora, Debian, Ubuntu), self-hosted NAS, Tailscale, Docker, computer architecture and hardware benchmarking
I post AI and developer-focused content on Instagram and YouTube under @adityaguha_, covering local LLM builds, benchmarking, and practical AI engineering.
- GDSC Chapter Lead (2023-24)
- PR Executive, BVDU DET
- Campus Executive, GeeksforGeeks
📫 adityaaguha@gmail.com | 📞 +91 7304748055 | adityaguha.tech