Build Physical Rigs. Collect Real-World Sensor Data. Deploy TinyML on Silicon.About the Role & The Reality AI LabThe Renesas AIoT Center of Excellence in Columbia, MD (formerly Reality AI) is seeking a hands-on Senior Edge AI Applications Engineer to build and deploy edge AI solutions that integrate machine learning with real-world hardware systems.In this role, you will work directly in our physical lab facility, executing proof-of-concept (PoC) hardware builds, assembling custom sensor setups, and deploying low-power ML models onto microcontrollers. You will operate at the exact intersection of small-scale physical fabrication, digital signal processing (DSP), C/C embedded firmware, and microcontroller-level TinyML deployment.You will execute non-visual sensing solutions - instrumenting physical hardware setups (industrial motors, automotive systems, consumer devices), collecting high-frequency time-series sensor data, building custom DSP pipelines, and optimizing tiny machine learning models to run on Renesas silicon.Are you an Embedded Engineer or Applied Physicist who thrives in a physical lab environment building custom sensor rigs, soldering prototype boards, and squeezing machine learning models onto microcontrollers?ATTENTION APPLICANTS: READ BEFORE APPLYINGThis is a physical lab execution and embedded hardware role.DO NOT APPLY if your background is strictly in Cloud AI, Data Science, Generative AI, LLMs, LangChain, or Web Backend APIs.DO APPLY if you have 2–3+ years of experience building physical prototype rigs, writing embedded C/C, running FFTs on raw accelerometer/acoustic data, debugging SPI/I2C signals with an oscilloscope, and running TinyML on bare-metal silicon.Key ResponsibilitiesPhysical Prototyping & Fabrication: Hands-on assembly of prototype rigs, sensor arrays, 3D-printed mounts, and microelectronic setups to capture real-world physical data.High-Frequency Sensor Data Engineering: Instrument physical systems to capture, clean, and preprocess high-frequency time-series datasets (acoustic, vibration, electrical, motor current).DSP & TinyML Deployment: Build DSP feature extraction pipelines (FFTs, spectral analysis, filtering) and deploy optimized, quantized TinyML models onto microcontrollers (ARM Cortex-M, Renesas RA/RX/RL78) using TFLite Micro, CMSIS-NN, or eIQ.Embedded Firmware Development: Write real-time C/C firmware, bare-metal or RTOS drivers (FreeRTOS, Zephyr), DMA buffer management, and low-level peripheral communication (SPI, I2C, UART, CAN).Customer & Cross-BU Collaboration: Work directly with customers and internal product teams to ingest raw hardware telemetry, debug edge firmware issues, and demonstrate working hardware solutions.Technical Leadership & Mentorship: Lead junior engineers on lab tasks, document engineering best practices, and contribute technical leadership across cross-functional teams.Why Join Renesas?No SCIF / No Clearance: Enjoy complex signal processing and hardware challenges without defense contractor bureaucracy or classified workspace restrictions.Commercial Product Impact: What you build in our lab gets integrated into Renesas silicon and deployed into millions of industrial, automotive, and consumer devices globally.Startup Autonomy + Global Backing: Small-team environment (under 50 people in Columbia) backed by one of the world's premier semiconductor manufacturers.
