10/07/2026 updated
100 % available
Embedded Systems Engineer | Embedded C, Electronics, AUTOSAR & HW/SW Integration
Zadar, Croatia
Germany +4
Dipl.-Ing. Electrical Engineering & Information Technology | PhD in Automotive Mechatronicsinfo: Germany, Austria, Switzerland, USA, Croatia
About me
Embedded Systems Engineer with expertise in Embedded C, electronics, sensor systems and hardware/software integration. Experienced in AUTOSAR Classic, automotive diagnostics, testing, PCB development and embedded system design. My strength is the combination of software and hardware expertise.
Testing (Software)Systems EngineeringTest AutomationUnit TestingAutomotive ElectronicsAUTomotive Open System Architecture (AUTOSAR)CAN BusNetwork SocketsDebuggingEmbedded CEmbedded SystemsLinux On Embedded SystemsEmbedded Operating SystemsEmbedded SoftwareFirmware
I am an Embedded Systems Engineer with a strong background in embedded software, electronics, sensor systems, and hardware/software integration. My work combines Systems Engineering with hands-on development, allowing me to move from system-level analysis and Software Architecture to implementation, testing, debugging, and integration of complete embedded systems.
On the software side, I develop Embedded C firmware for microcontroller-based platforms, including Bare Metal and real-time embedded systems as well as Linux on Embedded Systems. My work includes Embedded Software design, MISRA C-oriented development, Unit Testing, Test Automation, Software Testing, System Integration Testing, Test Engineering, Debugging, Root Cause Analysis, and communication software using CAN Bus, TCP/IP, Network Sockets, Serial Peripheral Interface (SPI), RS-485 Standard and UART.
In the automotive industry, I gained professional experience in Automotive Open System Architecture (AUTOSAR Classic), particularly in diagnostic software components. I worked with the Diagnostic Communication Manager (DCM), Diagnostic Event Manager (DEM), UDS diagnostics, variant management, unit and integration testing, debugging, and Automotive SPICE-oriented development processes. This experience gives me a solid basis for projects involving AUTOSAR, automotive diagnostics, CAN-based communication, and embedded automotive electronics.
My hardware background includes Hardware Design, PCB Layout and development, Mixed Signal Design, prototyping, sensor interfaces, Signal Conditioning, data acquisition, measurement, and Hardware Debugging. I have developed high-sampling-rate magnetic Sensor Systems in which custom electronics, firmware, communication interfaces, Signal Processing, sensor calibration, and systematic troubleshooting had to work together as one system.
In research and robotics projects, I integrated embedded electronics and high-speed sensor systems with robotic and mobile-robot platforms. I also developed an assistance system for vehicle alignment in inductive EV charging applications, combining embedded firmware, electronics, sensing, communication, and system-level integration.
A particular strength of my profile is Systems Integration across abstraction levels. I am comfortable tracing problems from application software and communication interfaces down through firmware, PCB-level electronics, mixed-signal circuits, and physical sensor behavior. This combination of Embedded Software, Hardware Design, Sensor Systems, System Integration, Testing, and Root Cause Analysis enables me to identify practical solutions without treating hardware and software as isolated domains.
Experience
Professional experience10+ years
Freelancer since2026
Languages
GermanNative speakerEnglishFluentSpanishBasic knowledgeCroatianNative speaker
Project history
I developed a custom embedded magnetic sensor system for robotics and UAV applications. The work included the design and implementation sensor electronics, microcontroller firmware, and high-speed data acquisition. Distributed magnetic sensor arrays were operated at sampling rates of up to 1 kHz, using SPI communication at up to 20 MHz. Particular focus was placed on reliable high-speed communication, hardware/software integration, and experimental validation.
For robotic applications, I developed a real-time motion control approach for a Franka Emika robot based on magnetic gradiometer data of the previously developed magnetic sensor system. Gradient tensor contractions were used to derive Cartesian linear and angular velocity commands for tracking the position and orientation of magnetic target. The Cartesian motion commands were transformed into joint velocities using inverse Jacobian kinematics. The motion model was specifically designed to operate with a 6×6 Jacobian, allowing direct matrix inversion.
The complete sensor-to-motion processing chain was implemented to meet the robot's strict real-time requirements, with control computations executing in less than 1 ms.
The developed systems were used for precise robot control and human-machine interaction based on magnetic gradiometry, as well as for UAV navigation using magnetic field measurements in the vicinity of high-voltage power lines.
Project prototype:
https://www.youtube.com/watch?v=hjXEnHwqsKw&t=88s
Magnetic Field-Based Driver Assistance System for Inductive EV Charging
Development of a magnetic field-based driver assistance system for precise vehicle alignment over inductive charging coils. The system used pulsed magnetic fields generated by the charging infrastructure to determine the relative position of the vehicle to the ground-side charging coil. The estimated position was provided to the driver to support accurate vehicle alignment for inductive charging.
The work covered the development and evaluation of the magnetic sensing concept, embedded signal processing and real-time position estimation algorithms, prototyping, system integration, and experimental validation. Particular focus was placed on computationally efficient algorithms suitable for execution on embedded hardware and reliable position estimation under real-world conditions.
As part of the project, the alignment system was integrated into a Mercedes-Benz B-Class Electric Drive (B 250) for Daimler AG, enabling validation and demonstration of the driver assistance concept in a real vehicle environment. The prototype was demonstrated at Hannover Messe and presented to the international automotive engineering community at the SAE J2954 Main Taskforce Meeting hosted by Audi AG in Ingolstadt, Germany (Jan. 2017).
The project combined magnetic sensing, embedded systems, signal processing, and automotive system integration to implement a complete positioning and driver assistance solution.
Embedded Measurement & Data Logging System for Electric Vehicle Fleet
Development of an embedded measurement and data-logging system for continuous sensor and vehicle data acquisition across a fleet of electric vehicles.
I was responsible for the architecture and design of the embedded software component system as well as the development, maintenance, testing, and commissioning of the bare-metal firmware running on the central data-logging unit. The work involved close collaboration with the hardware engineers developing the custom electronic control unit, requiring continuous coordination of hardware/software interfaces and system behavior.
The system was integrated and tested across multiple electric vehicle platforms and subsequently maintained and extended with additional functionality. Particular focus was placed on reliable acquisition and logging of vehicle, battery, and auxiliary-system data under real-world operating conditions.
The collected fleet data provided the basis for subsequent research and optimization of electric vehicle energy consumption, including the influence of auxiliary loads such as heating and air conditioning. Battery data was also used for battery modeling and the estimation of parameters such as State of Charge (SoC) and State of Health (SoH).