At Crossing Hurdles, we work as a referral partner. We refer candidates to our client, which collaborates with the world’s leading AI research labs to build and train cutting-edge AI models.

Position: IoT, Embedded & Firmware Engineering – AI Trainer

Type: Contract (Part-time or Full-time, Remote)

Compensation: Competitive (hourly / per task)

Location: Remote

Duration: Flexible, asynchronous

Requirements: (Training support will be provided)

Strong professional experience in IoT, Embedded Systems, or Firmware Engineering
Strong proficiency in embedded systems programming using C, C++, Rust, or Assembly
Solid understanding of RTOS, device drivers, memory management, and real-time constraints
Hands-on experience with hardware–software integration involving sensors, actuators, and communication modules
In-depth knowledge of wireless connectivity and IoT protocols such as Bluetooth/BLE, Wi-Fi, Zigbee, LoRaWAN, MQTT, Modbus, and CAN
Experience with secure device-to-cloud communication and IoT system architectures
Advanced debugging and optimization skills using tools such as oscilloscopes, logic analyzers, JTAG, and hardware profilers
Strong problem-solving and analytical skills for embedded and firmware-level challenges
Excellent written and verbal communication skills
Ability to work independently in a remote, collaborative environment
(Preferred) Academic background in Electrical Engineering, Computer Engineering, Embedded Systems, Electronics, Mechatronics, or Computer Science
(Preferred) Experience creating or delivering technical training or instructional content
(Preferred) Familiarity with AI or machine learning workflows applied to embedded or IoT systems

Role Responsibilities:

Translate real-world IoT, embedded, and firmware engineering workflows into structured AI training scenarios
Develop and review AI training content focused on embedded programming, firmware design, and system integration
Analyze complex hardware–software interaction scenarios to support AI model learning
Annotate and validate real-world development cases involving IoT protocols and connectivity challenges
Review AI-generated technical outputs for accuracy, completeness, and industry relevance
Provide actionable feedback to improve AI-driven training materials and datasets
Apply hands-on debugging and optimization expertise to enrich AI model understanding
Communicate technical concepts clearly to both technical and non-technical stakeholders

Application process: (Takes 7–30 mins)