Machine Learning Engineer

Qualifications

Bachelor’s degree in Electronics Engineering, Mechatronics, Electrical & Electronics Engineering, or a related field
Minimum 2 years of experience in electronic hardware or embedded systems development
Proficiency in C/C++ for embedded programming (STM32, ESP32, or similar microcontrollers)
Experience with communication protocols such as SPI, I2C, UART, CAN, Modbus
Proficiency in debugging tools (e.g., ST-Link, logic analyzer, oscilloscope)
Experience in firmware-hardware co-debugging and validation
Solid foundation in analog and digital circuit design and PCB design (Altium Designer, KiCad, or Eagle)
Ability to document hardware, firmware, and test procedures clearly and systematically
Experience in testing and debugging using multimeters, oscilloscopes, and signal generators
Strong analytical and troubleshooting abilities
Comfortable working in a multidisciplinary R&D team environment
No military obligation for male candidates
Residing in Istanbul

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Job Description

Design, develop, and test electronic hardware and embedded systems for logistics automation and technology projects
Support mechanical design tasks including enclosure design and 3D prototyping when needed
Develop and maintain firmware for embedded platforms (bare-metal or RTOS-based)
Conduct hardware validation, system integration, and performance testing
Collaborate with cross-functional teams in automation, mechanical, and software domains
Prepare and maintain technical documentation, BOMs, schematics, and test reports
Participate in R&D innovation projects aimed at improving logistics efficiency and sustainability
Ensure compliance with relevant standards (CE, FCC, EMC/EMI)
Manage version control and project documentation using Git and project tracking tools (Jira, Trello, Notion)

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Nice to Have

Experience with IoT systems (MQTT, HTTP, RESTful APIs)
Knowledge of wireless communication protocols (BLE, Wi-Fi, UWB)
Python scripting for automation or testing
Exposure to industrial automation (PLC programming, sensor integration, Modbus/CANopen communication)

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