Rubén Jiménez Mejías
Robotics engineer — end-to-end on real hardware.
I build robots from the chassis up — mechanical, electronics, embedded firmware, and high-level software. My current project is an autonomous outdoor kart; same toolkit applies to manipulators, drones, mobile robots, surgical robotics, or any platform where the layers have to actually work together. I find my best work happens where they meet.
Stack: CAD · 3D printing · steel welding · carbon fiber · custom PCBs · BMS · ESP32 · STM32 · FreeRTOS · ROS 2 · perception · control · Linux/Jetson.
Currently finishing my degree and looking for robotics roles in Switzerland.
LinkedIn GitHub Resume (EN) CV (ES)
Projects
Driverless Kart Flagship project
A real Tony Kart converted into a ROS 2 outdoor autonomous testbed. Jetson AGX Orin + ZED 2 stereo + custom ESP32 safety MCU, in-house steering actuation, custom emergency-brake system, custom wheel sensor PCB. First completed 5 laps autonomously on a cone-defined track in April 2025; manual mode fully operational, autonomous mode actively integrated.
Tech: ROS 2 Humble, YOLOv5, Jetson, Linux/RT, ESP32 / FreeRTOS, custom PCBs, planetary gear design, pneumatics
Partle — agent-native marketplace
Marketplace platform built for AI agents as first-class users: a public MCP server lets agents search products, list items for sale, and broker purchases on a user's behalf — a substrate for agent-managed shopping, ads, and listings. Passkey auth, interactive map, Elasticsearch, community reliability ratings. Live service.
Tech: React/TypeScript, FastAPI, PostgreSQL, Elasticsearch, Leaflet, FIDO2 passkeys, MCP server
Cyberwheel — open-source EUC
Electric unicycle that "never cuts power," addressing critical safety concerns in commercial products. Sealed electronics, crash-resistant, fully open hardware + firmware.
Tech: Embedded systems, motor control, BMS, mechanical design
Investment Analysis — systematic stock valuation
Configuration-driven framework for stock analysis. Multiple valuation models (DCF, RIM) plus an LSTM/Transformer neural network at 78.64% accuracy across 500+ S&P 500 stocks.
Tech: Python, PyTorch, SQLite, Pandas, financial modelling
Also on: GrabCAD