Embedded engineer. Edge AI practitioner.
I am currently a Debug Engineer Intern at Jabil in my final semester of B.Tech Electronics & Telecommunication Engineering. My internship is focused on PCB-level fault isolation, power rail analysis, and root cause analysis on production assemblies across SMT and functional test stages.
On the firmware side, I write and debug Embedded C/C++ on ARM7 (LPC2148), STM32, and ESP8266 targets. I apply FreeRTOS concepts — task scheduling, queue-based inter-task communication, and binary semaphores — in system designs.
My Edge AI work is deployment-focused, not theoretical. I train lightweight classification models, convert them to TensorFlow Lite, and run inference on microcontroller-class hardware under real latency and memory constraints. I integrate AI inference engines with physical actuators through UART/serial pipelines.
I develop on Linux, use Git for version control, and build IoT data pipelines with MQTT, Firebase, and Python automation. My experience spans the full stack from bare-metal firmware to cloud dashboards.
AI deployed on hardware — not in notebooks.
- ›Computer Vision · OpenCV real-time processing
- ›Custom ML model training — gesture classification
- ›TensorFlow Lite on embedded targets
- ›Sub-200ms inference latency
- ›Model quantization (INT8 / FP16)
- ›UART bridge — AI engine ↔ microcontroller
Professional Timeline
Debug Engineer Intern
Jabil- ›PCB-level fault isolation and rework validation across SMT and assembly stages
- ›Power rail and signal integrity verification using oscilloscopes and DMMs
- ›Root cause analysis on production failures — component, solder, and assembly defects
- ›Test yield analysis and cross-functional debug coordination with Test & Quality teams
- ›Failure documentation, trend tracking, and debug knowledge base maintenance
IoT Intern
Acmegrade- ›Designed MQTT-based device-to-cloud communication pipelines
- ›Built real-time Firebase dashboards for sensor monitoring
- ›Automated sensor data acquisition with Python — 98% delivery reliability
- ›End-to-end IoT prototyping from embedded firmware to cloud visualization
Embedded Systems Intern
Indo German Tool Room- ›Developed ARM7 LPC2148 firmware in Embedded C for industrial control systems
- ›Implemented ADC, UART, and PWM-based peripheral control
- ›Debugged hardware interfaces using JTAG and logic analyzers
- ›Validated SPI, I2C, and UART peripheral-level communication
Featured AI-Integrated Work
Camera-based hand gesture recognition driving Arduino actuators via UART. MediaPipe landmarks → custom classifier → serial actuation pipeline.
Flex-sensor glove streams ADC data to a Python ML pipeline. Firmware handles sampling; Python handles inference and text output.
Integrated Engineering Stack
From bare-metal hardware to intelligent edge inference — built layer by layer.