Senior Embedded Applications Engineer, Tiny ML Lab

• Full-time
• Employment Type:
  
  Regular (PERM)
• Remote Work Available:
  No

Renesas is one of the top global semiconductor companies in the world. We strive to develop a safer, healthier, greener, and smarter world, and our goal is to make every endpoint intelligent by offering product solutions in the automotive, industrial, infrastructure and IoT markets. Our robust product portfolio includes world leading MCUs, SoCs, Analog and power products, plus Winning Combination solutions that curate these complementary products.

We are a key supplier to the world’s leading manufacturers of electronics you rely on every day; you may not see our products, but they are all around you.
Renesas employs roughly 21,000 people in more than 30 countries worldwide. As a global team, our employees actively embody the Renesas Culture, our guiding principles based on five key elements:
Transparent, Agile, Global, Innovative, and Entrepreneurial. Renesas believes in, and has a commitment to, diversity and inclusion, with initiatives and a leadership team dedicated to its resources and values. At Renesas, we want to build a sustainable future where technology helps make our lives easier. Join us and build your future by being part of what’s next in electronics and the world.

Build Physical Rigs. Collect Real-World Sensor Data. Deploy TinyML on Silicon.

About the Role & The Reality AI Lab

The 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?

Key Responsibilities

Physical 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…