IoT, Embedded & Firmware Engineering - AI Trainer

IoT, Embedded & Firmware Engineering - AI Trainer

Job Summary:

Join our customer's team as an IoT, Embedded & Firmware Engineering - AI Trainer, where your deep technical expertise will contribute directly to AI-driven training initiatives. You will help shape the future of embedded systems by sharing your industry experience and guiding the development of intelligent firmware solutions. This is a unique opportunity to impact AI training for next-generation IoT and embedded platforms from anywhere in the world.

Key Responsibilities:

• Develop and deliver technical content for AI-based training focused on IoT, embedded, and firmware engineering domains.

• Analyze and break down complex embedded and hardware–software integration scenarios to facilitate AI model learning.

• Collaborate with cross-functional teams to define data requirements and annotate real-world development cases.

• Validate and review technical data to ensure accuracy and comprehensive coverage of relevant IoT protocols, connectivity, and system integration challenges.

• Provide actionable feedback to improve AI-driven training materials and digital platforms.

• Leverage hands-on experience in debugging and optimizing embedded systems to enrich AI model capabilities.

• Communicate technical concepts clearly, both in writing and verbally, to support global teams and documentation efforts.

Required Skills and Qualifications:

• Minimum 3 years of professional experience in IoT, Embedded & Firmware Engineering.

• Proficiency in low-level programming for microcontrollers and SoCs using C, C++, Rust, or Assembly.

• Solid understanding of RTOS, device drivers, memory management, and real-time embedded system constraints.

• Demonstrated expertise interfacing firmware with diverse hardware components: sensors, actuators, communication modules, and power systems.

• In-depth knowledge of wireless communication protocols such as Bluetooth/BLE, Wi-Fi, Zigbee, LoRaWAN, MQTT, Modbus, CAN, and secure device-to-cloud communication.

• Advanced skills in debugging and optimization using oscilloscopes, logic analyzers, JTAG, and hardware profiling tools.

• Excellent written and verbal communication skills, with a strong attention to detail.

Preferred Qualifications:

• Academic background in Electrical Engineering, Computer Engineering, Embedded Systems, Electronics, Mechatronics, or Computer Science with embedded/low-level focus.

• Experience creating or delivering technical training content for professional or academic audiences.

• Familiarity with AI or ML workflows as applied to embedded engineering contexts.