Meenakshi Menchu

Embedded Software Engineer with 4+ years of experience in firmware development, device driver programming, and real-time embedded systems for industrial automation and edge AI applications. Proven expertise in C/C++, Python, and ARM Cortex-M/A architectures with hands-on experience in RTOS (FreeRTOS, Zephyr), Linux kernel programming, and low-level hardware interfacing. Specialized in developing IoT-enabled embedded solutions, implementing communication protocols (I2C, SPI, UART, CAN, Ethernet), and optimizing code for memory-constrained environments.

Skilled in embedded Linux, Yocto Project, device tree configuration, and BSP porting. Experienced in edge AI/ML inference on resource-constrained devices, sensor integration, and firmware over-the-air (FOTA) updates. Passionate about building reliable, secure, and power-efficient embedded systems from concept to production.

Embedded Software Engineer - Emerson - Round Rock, TX

(2024-07)

• Designed and developed firmware for industrial control systems using ARM Cortex-M7 microcontrollers, implementing real-time data acquisition and processing for process automation applications, achieving 99.9% system reliability.
• Integrated Modbus TCP/IP and CANopen communication protocols for seamless connectivity with PLCs, HMIs, and SCADA systems, reducing integration time by 30% for field deployments.
• Implemented secure boot and firmware over-the-air (FOTA) update mechanisms using AES-256 encryption and digital signatures, ensuring secure firmware delivery and reducing manual update efforts by 60%.
• Developed device drivers for analog/digital sensors (temperature, pressure, flow, vibration) with interrupt-driven and DMA-based data acquisition, achieving precise real-time monitoring with ±0.1% accuracy.
• Built predictive maintenance capabilities using Python-based edge analytics, processing vibration and temperature data to detect anomalies, reducing unplanned downtime by 25% for critical equipment.
• Optimized RTOS task scheduling and memory allocation for time-critical control loops (50µs interrupt latency), reducing CPU utilization by 20% through efficient task prioritization and interrupt management.
• Designed redundant communication architecture with failover mechanisms using dual Ethernet ports and CAN bus, achieving zero downtime during network switchovers and ensuring industrial-grade reliability.
• Created comprehensive unit and integration test frameworks using CppUTest, automating regression testing and reducing post-release defects by 40% across firmware releases.
• Collaborated with hardware teams on PCB design reviews, providing firmware perspective to optimize component selection, pin assignments, and power distribution for efficient embedded system design.

Embedded Software Engineer - Syntiant Corp - India

(2022-09 - 2023-12)

• Developed and optimized edge AI inference engines for voice recognition and sensor fusion applications on ARM Cortex-M4 and ESP32 platforms, achieving 90% accuracy with 5ms inference latency on 20KB RAM devices.
• Ported and optimized TensorFlow Lite Micro models for neural processing unit (NPU) acceleration, reducing inference time by 70% and power consumption by 50% compared to CPU-only execution.
• Built BLE-based sensor nodes for wearable health monitoring, implementing low-power firmware with I2C/SPI sensor drivers and custom BLE GATT services, achieving 30-day battery life from 50mAh coin cell.
• Developed multithreaded Zephyr RTOS applications with priority-based scheduling for concurrent sensor data acquisition, edge inference, and wireless communication, ensuring deterministic 10ms response time for time-sensitive tasks.
• Integrated multiple sensor modalities (microphone, accelerometer, gyroscope, heart rate) using efficient data fusion algorithms, improving environmental context detection accuracy by 40%.
• Implemented over-the-air (OTA) firmware updates via BLE using Zephyr's MCUboot, enabling remote device upgrades and reducing field return rates by 45% with rollback capabilities.
• Created automated test infrastructure using Python and pytest for edge device validation, including regression and performance testing across 50+ device variants, reducing manual QA effort by 70%.
• Designed and optimized power management firmware using Zephyr power management APIs, implementing multiple low-power states (sleep, deep sleep, off) and wake-on-interrupt for event-driven operation.
• Collaborated with ML engineers to quantize, prune, and convert neural network models for embedded deployment, maintaining model accuracy within 2% of floating-point versions.

Master of Science - Computer Science - Kent State University

Bachelor of Technology - Electronics and Communication Engineering - Jawaharlal Nehru Technological University