Tomáš Juřica

Prague & Brno, Czech Republic · +420 774 989 814 · tomasjuri@gmail.com

Computer-vision and machine-learning engineer focused on bringing cutting-edge CV and embedded-AI solutions from research to real-world products. Passionate life-long learner with solid academic background and hands-on experience designing, training and optimising deep-learning models for high-performance deployment. I actively leverage artificial intelligence tools (including generative AI) to maximise my productivity – efficiency is my key objective.

Experience

Machine Learning Engineer

Veracity Protocol

I developed and deployed cutting-edge AI solutions for visual verification and authentication of physical objects, specializing in computer vision models for PCB manipulation analysis and collectible item authentication. My expertise spans the entire ML pipeline from data processing and dataset preparation to advanced model training for material and ID card authenticity verification.

I led the development and deployment of a large-scale hardware scanner solution for collectible cards authentication in warehouse environments, managing the complete project lifecycle including shipping, integration, remote maintenance, and monitoring. I presented solutions for PCB authentication and physical tampering detection at customer conference in San Francisco, demonstrating the commercial impact of our technology.

I created extensive datasets and managed large-scale data collection efforts for training authentication models using Pandas for data processing and MongoDB for dataset management. My work involved implementing sophisticated data augmentation and filtration pipelines using Albumentations framework to ensure high-quality training data for various authentication tasks.

My technical optimization work included developing and optimizing deep learning models using EfficientNet and ResNet architectures, then optimizing them with TensorRT and ONNX for high-performance inference, and specifically optimizing code for NVIDIA Jetson embedded platforms, gaining extensive experience with this edge computing ecosystem. I designed robust camera integration systems for production environments.

Utilizing my hardware skills, I designed and manufactured custom camera holders and mechanical parts to industrialize our solutions. I oversaw hardware design and deployment in customer production facilities with comprehensive remote maintenance and monitoring capabilities, bridging the gap between research prototypes and production-ready systems.

Mar 2019 – Jul 2025

Computer Vision & Machine Learning Engineer

Innovatrics

As a core member of the AI research team, I contributed to the development of state-of-the-art face recognition algorithms and biometric identification systems using TensorFlow, PyTorch, and Caffe frameworks. My responsibilities encompassed the entire machine learning workflow, from designing robust data pipelines and curating high-quality datasets to training and optimizing advanced AI algorithms for production deployment.

I played a key role in transitioning computer vision technology from research to manufacturing applications, with a particular focus on automated visual inspection systems. My most significant contribution was implementing and optimizing Mask R-CNN semantic segmentation models for defect detection in manufacturing processes, specifically for precision quality control of ID cards.

This work involved extensive development of segmentation and detection algorithms and creating custom dataset management tools and annotation frameworks specifically designed for the unique requirements of our applications, contributing directly to the company's expansion into industrial AI applications.

Jan 2017 – Feb 2019

Computer Vision Engineer

NXP Semiconductors

My main responsibility was the implementation and optimization of computer-vision algorithms for embedded processors such as i.MX6 and i.MX8, primarily targeting ADAS applications. I focused on developing efficient algorithms using OpenCL and Vivante SDK that could leverage the limited computational resources of embedded systems while integrating with MIPI camera interfaces.

My biggest achievement was developing an optimized stereo-vision algorithm for depth estimation and 3D reconstruction applications, achieving state-of-the-art real-time FPS performance on an embedded GPGPU. This work involved low-level C++ optimization techniques and parallel computing strategies to maximize performance on resource-constrained hardware.

Jul 2016 – Dec 2017

Education

Brno University of Technology, Faculty of Information Technology

Master of Science – Embedded Systems

Thesis: Machine-learning visual inspection and defect-detection in manufacturing.

Sep 2016 – Jun 2019

Brno University of Technology, Faculty of Information Technology

Bachelor of Science – Computer Science

Bachelor thesis: "Vehicle speed measurement using a stationary camera". I joined the faculty's research team and contributed to the development of a computer-vision system for measuring vehicle speeds.

Sep 2013 – Jun 2016

Awards & Certifications

Skills

Programming Languages & Tools
Key Competencies
  • Deep Learning – TensorFlow, Keras, PyTorch, ONNX, TensorRT, TensorBoard
  • Computer Vision – OpenCV, PIL/Pillow, scikit-image, Image Segmentation, Object Detection, Camera Calibration, Stereo Vision
  • Programming – Python, C/C++, CUDA, OpenCL, Bash, Git
  • Dev & Ops – Docker, Linux, AWS, Agile / Scrum
  • ML Engineering – FastAPI, Flask, Jupyter Notebooks
  • Classical ML & Data – scikit-learn, Pandas, NumPy, Scipy, Matplotlib/Seaborn
  • Edge Deployment – NVIDIA Jetson SDK
  • Infrastructure – Docker Compose, AWS
  • GenAI – Hugging Face Transformers, Diffusers
  • Detection & Segmentation – YOLO, Mask R-CNN
  • Computer Graphics – OpenGL, Vulkan
  • C/C++ Build – CMake
  • MATLAB – Data processing & prototyping
Languages
  • English – C1 (Advanced)
  • Czech – Native
  • German – B2 (Upper-intermediate)
  • Spanish – A1–A2 (Beginner)

Interests

Areas & Hobbies
  • Machine learning & artificial intelligence
  • Computer vision & new technologies
  • 3D printing & CAD design – built my own open-source 3D printer from hobby-shop parts; enjoy designing hardware parts such as camera and phone holders
  • Sports – jogging, cycling & weightlifting
  • Travelling & outdoor activities
About
Experience
Education
Awards & Certifications
Skills
Interests

Tomáš Juřica

Prague & Brno, Czech Republic · +420 774 989 814 · tomasjuri@gmail.com
Computer-vision and machine-learning engineer focused on bringing cutting-edge CV and embedded-AI solutions from research to real-world products. Passionate life-long learner with solid academic background and hands-on experience designing, training and optimising deep-learning models for high-performance deployment. I actively leverage artificial intelligence tools (including generative AI) to maximise my productivity – efficiency is my key objective.
LinkedIn Profile GitHub Profile

Experience

Machine Learning Engineer

Mar 2019 – Jul 2025
Veracity Protocol
I developed cutting-edge AI solutions for visual verification and authentication of physical objects, specializing in computer vision models for PCB manipulation analysis and collectible item authentication. I led development of a large-scale hardware scanner solution for warehouse authentication, managing complete project lifecycle from design to deployment. I presented solutions for PCB authentication and physical tampering detection at customer conference in San Francisco. My technical work included dataset creation, model optimization with TensorRT and ONNX for NVIDIA Jetson platforms, and designing custom camera holders and mechanical parts to industrialize solutions. I bridged research prototypes with production-ready systems for customers.

Computer Vision & Machine Learning Engineer

Jan 2017 – Feb 2019
Innovatrics
R&D team member focusing on ML models and datasets for face-recognition. Contributed to automated visual inspection projects using Mask R-CNN for IC card defect segmentation.

Computer Vision Engineer

Jul 2016 – Dec 2017
NXP Semiconductors
Implemented and optimized computer-vision algorithms for embedded processors (i.MX6, i.MX8). Achieved state-of-the-art real-time stereo-vision performance on embedded GPGPU.

Education

Brno University of Technology, Faculty of Information Technology

Sep 2016 – Jun 2019
Master of Science – Embedded Systems
Thesis: Machine-learning visual inspection and defect-detection in manufacturing.

Brno University of Technology, Faculty of Information Technology

Sep 2013 – Jun 2016
Bachelor of Science – Computer Science
Bachelor thesis: "Vehicle speed measurement using a stationary camera". I joined the faculty's research team and contributed to the development of a computer-vision system for measuring vehicle speeds.

Awards & Certifications

Generative AI with Large Language Models – DeepLearning.AI & AWS (Jun 2025)
Apply Generative Adversarial Networks (GANs)
Build Better Generative Adversarial Networks (GANs)
Generative Adversarial Networks (GANs)
Natural Language Processing Specialization – DeepLearning.AI
Build Basic Generative Adversarial Networks (GANs)
Natural Language Processing with Attention Models
Natural Language Processing with Sequence Models
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Natural Language Processing with Classification and Vector Spaces – DeepLearning.AI (Sep 2020)
Natural Language Processing with Probabilistic Models
Deep Learning Specialization – DeepLearning.AI
Sequence Models – DeepLearning.AI (Jan 2019)
Convolutional Neural Networks – DeepLearning.AI (Dec 2018)
Improving Deep Neural Networks – DeepLearning.AI (Dec 2018)
Neural Networks and Deep Learning
Structuring Machine Learning Projects

Skills

Programming Languages & Tools

Key Competencies

Deep Learning – TensorFlow, Keras, PyTorch, ONNX, TensorRT
Computer Vision – OpenCV, Image Segmentation, Object Detection, Camera Calibration, Stereo Vision
Programming – Python, C/C++, CUDA, OpenCL, Bash, Git
Dev & Ops – Docker, Linux, AWS, Agile / Scrum
ML Engineering – FastAPI, Flask (REST inference APIs)
Classical ML & Data – scikit-learn, pandas, NumPy
Edge Deployment – NVIDIA Jetson SDK, DeepStream
Infrastructure – Docker Compose, AWS S3 / Lambda / SageMaker
GenAI – Hugging Face Transformers, Diffusers
Detection & Segmentation – YOLO, Mask R-CNN
Computer Graphics – OpenGL, Vulkan
C/C++ Build – CMake, Conan
MATLAB – Data processing & prototyping

Languages

English – C1 (Advanced)
Czech – Native
German – B2 (Upper-intermediate)
Spanish – A1–A2 (Beginner)

Interests

Machine learning & artificial intelligence
Computer vision & new technologies
3D printing & CAD design – built my own open-source 3D printer from hobby-shop parts; enjoy designing hardware parts such as camera and phone holders
Sports – jogging, cycling & weightlifting
Travelling & outdoor activities