Ayman M.
Software Engineer @ZF Group
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WORK HISTORY
Software Engineer @ZF Group
Delivered real-time C++17 embedded software on Linux for safety-critical telematics systems, enabling deterministic, low-latency processing with optimized algorithms and high fleet reliability.* Improved motion detection and driver activity classification by 25-35% via sensor fusion and signal processing, increasing robustness under noisy real-world vehicle conditions.* Reduced CPU utilization and memory footprint by ~30% on multi-core embedded platforms using profiling-driven optimization, concurrency improvements, and parallelization for higher efficiency.* Implemented hardware-integrated modules (smart card, CAN, GNSS, sensors) meeting sub-millisecond timing constraints, ensuring reliability across heterogeneous hardware and real-time environments.* Built scalable Python/Qt5 data validation and processing services handling millions of records daily, improving observability and reducing manual operational effort by ~50% through automation.* Increased system reliability and engineering velocity by introducing automated testing, static analysis, and CI/CD, reducing incident rates and mean time to resolution by ~40% via root-cause analysis.
EDUCATION
Cairo University
B.Sc., Computer Science
ABOUT AYMAN M.
I am a Software Engineer specializing in real-time, safety-critical systems, with a strong foundation in C/C++, embedded Linux, and high-performance algorithm development. My experience spans telematics, ADAS, and data-intensive platforms, where I focus on building reliable, deterministic software that operates efficiently under strict latency and resource constraints.• In my work on embedded and automotive systems, I have delivered production-grade software for multi-core platforms, integrating hardware components such as CAN, GNSS, sensors, and smart cards while meeting sub-millisecond timing requirements. I’ve improved motion detection and driver activity classification accuracy through sensor fusion and signal processing, and reduced CPU and memory usage through profiling-driven optimization and parallelization.• Beyond embedded development, I design scalable backend and data processing solutions in Python, handling millions of records daily and significantly reducing manual operational effort through automation and observability improvements. I am passionate about engineering excellence—introducing automated testing, static analysis, and CI/CD practices that increase reliability, accelerate delivery, and reduce incident resolution time.• As an Algorithm Software Engineer, I have developed real-time collision avoidance and predictive modeling algorithms for ADAS platforms, built optimized 2D/3D visualization pipelines with OpenGL, and modernized legacy systems using modern C++ and modular architectures. I also enjoy improving developer productivity through robust build systems, reproducible workflows, and automation.
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