Embedded System Engineer

TinyML Embedded Engineer – Ultra-Low Power Remote Sensing Systems

Embedded Systems | TinyML | Remote Sensing

Are you an expert in machine learning at the edge eager to develop ultra-low power remote sensing devices?

We’re hiring for a leading company focused on intelligent embedded platforms for autonomous sensing in challenging environments. As a TinyML Embedded Engineer, you will lead the design and deployment of TinyML models on microcontrollers, optimizing firmware for real-time data processing and low-power operation.

You’ll work closely with sensor and hardware teams to ensure seamless integration and efficient power management for reliable field performance.

What You’ll Do:

• Develop and deploy TinyML models using frameworks like TensorFlow Lite for Microcontrollers or Edge Impulse

• Optimize inference pipelines for low-power MCUs (e.g., STM32, nRF52, Cortex-M4/M7)

• Implement real-time firmware for data collection, signal processing, and local decision-making

• Collaborate with sensor and hardware teams to align data I/O and power budgets

• Conduct field testing and benchmarking for model latency, power consumption, and reliability

Your Background:

• Strong expertise in embedded C/C++ and real-time systems

• Experience with ML model quantization, pruning, and on-device inference

• Familiarity with embedded toolchains and power profiling tools

• Bonus: Experience with TinyML in environmental monitoring, industrial IoT, or wearables

Bonus Points:

• Background in autonomous sensor platforms or off-grid remote sensing

• Knowledge of low-power design techniques for embedded systems

• Experience working in cross-disciplinary teams integrating ML and hardware