Embedded Systems Engineer – AI Time Series Forecasting
Location: Hybrid or Remote
Company: IoT That
Job Type: Full-Time
About the Role
We're seeking a skilled Embedded Systems Engineer with a strong background in time series forecasting and AI integration to join our R&D team. This role involves working on intelligent edge devices that process and predict sensor data using real-time machine learning algorithms, including models like Facebook Prophet. You will help design, implement, and optimize embedded solutions that integrate forecasting algorithms into low-power hardware environments for applications in [e.g., agriculture, energy, or industrial IoT].
Key Responsibilities
- Design, develop, and test embedded firmware (C/C++/Micro Python) for microcontroller-based platforms (e.g., STM32, ESP32, ARM Cortex-M)
- Integrate lightweight AI models and time series forecasting (e.g., Prophet) into embedded Linux or edge environments
- Work with time series sensor data (e.g., environmental, telemetry, telemetry) and apply preprocessing, compression, and ML inference
- Interface with cloud or edge pipelines for model training and deployment
- Collaborate cross-functionally with AI/ML engineers, data scientists, and hardware designers
- Optimize runtime memory, power consumption, and model execution on-device
Requirements
- BSc/MSc in Electrical Engineering, Computer Engineering, or related field
- 3+ years of experience in embedded systems development
- Proficiency in C/C++, RTOS, and embedded debugging
- Experience with Python-based ML libraries: Prophet, NumPy, Pandas, scikit-learn
- Solid understanding of time series data, statistical forecasting, and signal processing
- Familiarity with cross-compiling or deploying models to embedded Linux or microcontroller targets
- Experience working with serial/UART, I2C, SPI, ADC, and wireless protocols (Wi-Fi, BLE, LoRa)
Nice to Have
What We Offer
How to Apply
Send your resume, cover letter, and (if applicable) links to relevant projects or GitHub to:
info@iot-that.com