Jun 2025 – Nov 2025
Robotics / IoT Engineer
Robotics Stellar Skills Pvt Ltd
Work Contributions
- Deployed machine-learning models to the edge on ESP32 and Raspberry Pi platforms, optimised for real-time, offline inference without cloud dependency.
- Built IoT network topologies spanning Wi-Fi Mesh, BLE, and ESP-NOW to connect distributed sensor arrays to a MySQL-backed cloud/back-end environment.
- Integrated sensor front-ends with edge compute nodes and back-end services, keeping the physical, embedded, and cloud layers of each deployment aligned.
- Delivered technical instruction and hands-on troubleshooting on advanced robotics platforms, including LEGO EV3 and Spike Prime, in an educational / skills-development context.
- Provided embedded-system support during robotics activities, diagnosing hardware, firmware, and connectivity issues in real time.
Key Achievements
Ran ML inference offline on constrained edge hardware (ESP32, Raspberry Pi), avoiding the latency and connectivity cost of a cloud round-trip.
Bridged distributed sensor arrays to a MySQL back-end over Wi-Fi Mesh, BLE, and ESP-NOW — three distinct wireless transports — chosen per deployment for range, power, and topology needs.
Kept mixed IoT networks stable across the embedded, wireless, and cloud layers, resolving faults that spanned all three.
Supported multi-platform robotics sessions on LEGO EV3 and Spike Prime, diagnosing platform-specific hardware and firmware issues under time pressure.
Turned real deployment issues into teachable troubleshooting for trainees, reinforcing the link between embedded design decisions and observable system behaviour.