Robotics & Automation Engineer · AI / ML · Computer Vision · Local AI · Systems Engineering
I build intelligent systems by connecting perception → intelligence → planning → action across robotics, AI, software, and automation.
I’m strongest when a problem crosses boundaries: when a model has to become a product, when software has to understand hardware, or when multiple technical layers need to work together as one system.
| Area | What that means in practice | Technologies / concepts |
|---|---|---|
| 🤖 Robotics & Automation | Connecting sensing, decision logic, planning and physical action into a complete loop. | Robotics · Control Systems · PLC · Microcontrollers · Sensors · Automation |
| 🧠 AI / ML / LLMs | Building model-driven applications, prediction pipelines, agents and local inference systems. | Python · PyTorch · TensorFlow · Keras · LLMs · RAG · Agents · LoRA / QLoRA |
| 👁️ Computer Vision | Turning images and video into information that a larger system can reason about and act on. | OpenCV · Detection · Image Processing · Vision Pipelines |
| ⚙️ Local AI Infrastructure | Running models close to the machine, routing requests and designing around real hardware limits. | llama.cpp · GGUF · CUDA · Model Routing · Streaming · Hardware-aware inference |
| 🌐 Software Architecture | Designing the path from frontend → API → backend → model → storage so the system stays usable and debuggable. | FastAPI · React · Next.js · Electron · Vite · SQLite · TypeScript |
| 🔌 API & Systems Integration | Connecting different models, runtimes and services behind coherent developer-facing interfaces. | REST · OpenAI-compatible APIs · Anthropic Messages · SSE · HTTP |
| 🧪 Rapid Prototyping | Moving from experiment → working prototype → tested system → polished product. | Git · Linux · Docker · Testing · Benchmarking |
PERCEIVE → UNDERSTAND → PLAN → BUILD → TEST → SHIP
↓ ↓ ↓ ↓ ↓ ↓
signals models logic system failure usable
vision algorithms rules APIs analysis product
sensors inference tools UI metrics docs
I naturally think in systems rather than isolated components. A camera, model, API, database and interface are more useful when they form a reliable chain than when each piece is impressive on its own.
|
Systems thinking I break complex problems into interacting components, interfaces and feedback loops. |
Hardware awareness I think about VRAM, latency, compute limits, thermal constraints and the machine underneath the software. |
End-to-end ownership I’m comfortable moving between models, backend services, APIs, interfaces and deployment. |
| Debugging mindset I trace failures through the stack instead of patching only the visible symptom. |
Integration mindset I enjoy connecting technologies that normally live in separate layers. |
Product translation I try to turn technically difficult systems into something people can actually understand and use. |
| Performance awareness I balance quality, memory, latency, reliability and hardware constraints rather than optimizing one metric blindly. |
Experimentation I’m comfortable testing unfamiliar models, architectures and tools against real constraints. |
Learning velocity I learn the technology needed to solve the problem instead of forcing every problem into one familiar stack. |
| Project | What it demonstrates | Link / status |
|---|---|---|
| Infera | Local-first AI gateway that routes multiple model backends through familiar API contracts and a local browser workspace. | Repository · Live site |
| MeeraAI | Local desktop AI assistant with model orchestration, RAG, speech, tools and hardware-aware inference. | 🔒 Private R&D |
| AarnaAI | AI-assisted market analysis experiment using LSTM, Random Forest and technical indicators in an interactive interface. | 🔒 Private R&D |
| Autonomous AI Portfolio | Portfolio experience using local browser inference to make AI part of the interface itself. | Live |
| Binance Futures Testnet CLI | API engineering around signed requests, validation, error handling and deterministic request construction. | Repository |
Infera → API architecture, model routing, local infrastructure, streaming and developer experience.
MeeraAI → local AI orchestration, voice systems, RAG, tools, hardware-aware inference and desktop application architecture.
AarnaAI → ML experimentation, data pipelines, time-series modelling and turning quantitative ideas into usable interfaces.
Autonomous AI Portfolio → frontend engineering, browser inference, WebGPU and making an AI system part of the product itself.
Binance Futures Testnet CLI → practical API integration, cryptographic request signing, validation and failure-boundary thinking.
| How do I run useful AI locally? | Model choice, quantization, VRAM limits, runtimes, context, tools and latency. |
| How do I connect different AI backends? | Routing, adapters, normalized interfaces, compatibility layers and streaming. |
| How do I turn perception into action? | Vision / sensor input → inference → planning → control / automation. |
| How do I make complex systems understandable? | Good APIs, clean UI, observability, documentation and sensible architecture. |
| How do I make an experiment become a product? | Prototype → benchmark → debug → package → document → ship. |
Local AI · AI Agents · LLM Infrastructure · RAG · Model Routing · Computer Vision · Robotics · Autonomous Systems · Voice AI · Edge Inference · Human-AI Interfaces · Hardware-Aware AI
🌐 Portfolio · LinkedIn · ⚡ Infera · 🔐 Binance Testnet CLI · 🔬 ORCID
I build intelligent systems that connect perception, AI, software and automation — with a strong preference for local control, practical architecture and technology people can actually use.
Robotics · AI · Vision · Local Inference · Systems Engineering