Dávid Kocsis
Embedded Software Engineer
Győr
Summary
Innovative and results-driven Software Engineer with 3+ years of experience in embedded systems development, algorithm optimization, and automation within high-end automotive projects. Strong problem-solving skills, rapid learning ability, and solid expertise in Python, C++, and computer vision. Successfully designed and implemented high-performance simulation environments, introduced research-based algorithms, and significantly reduced debugging time through automated solutions. Open to opportunities in Artificial Intelligence and data-driven technologies, combining analytical thinking with hands-on development experience.
Overview
3
3
years of professional experience
6
6
years of post-secondary education
Work History
Medior Embedded Software Engineer
Robert Bosch GmbH
07.2022 - Current
- Developed and optimized camera-based localization systems for premium vehicle parking functions.
- Improved algorithm performance and reduced error rates by introducing new, research-driven solutions.
- Designed and implemented a high-speed simulation environment, significantly accelerating debugging and issue resolution.
- Served as KPI owner: implemented automated data collection and evaluation scripts, created visualization tools, managed requirements, performed evaluations, and delivered presentations.
- Contributed to the Guidance module by developing and testing new algorithms, benchmarking them against existing solutions, and creating performance visualizations.
- Analyzed vehicle test data, and implemented visualization and processing scripts in Python.
- Created multiple automation scripts, streamlining development workflows, and reducing testing cycles.
Education
Master of Science - Computer Science
Széchenyi István Egyetem
Győr 02.2023 - 07.2024
Bachelor of Science - Computer Science
Széchenyi István Egyetem
Győr 09.2018 - 01.2023
Skills
Programming languages: Proficient in Python and C/C
Tools & Frameworks: Git, Docker, CMake, NumPy, Pandas, Matplotlib, OpenCV, PyTorch
Embedded Systems: Real-time software development, sensor data processing, algorithm optimization
Artificial Intelligence & Machine Learning: Implementation and evaluation of ML models, computer vision algorithms, deep learning architectures
Data Processing & Visualization: KPI calculation, data analysis, interactive dashboards, automated reporting
Simulation & Testing: Custom simulation environments, automated test pipelines
Other Skills: Requirement management, performance evaluation, technical presentations
Languages: Hungarian (native), English (fluent)
Additional projects
- Automatic Number Plate Recognition (ANPR) – BSc Thesis
Implemented a TensorFlow-based neural network for license plate detection and OCR-based character recognition. Prepared and augmented datasets, trained the model, and integrated OpenCV image processing algorithms to improve accuracy. - Asphalt and Lane Detection with Semantic Segmentation – MSc Thesis
Developed a PyTorch-based deep learning model for asphalt surface detection, achieving high accuracy even on low-quality datasets. Applied computer vision algorithms (NumPy, OpenCV) for lane detection on the segmented surfaces. Gained extensive experience in neural network development, image processing, and model evaluation.
Timeline
Master of Science - Computer Science
Széchenyi István Egyetem
02.2023 - 07.2024
Medior Embedded Software Engineer
Robert Bosch GmbH
07.2022 - Current
Bachelor of Science - Computer Science
Széchenyi István Egyetem
09.2018 - 01.2023