Tom is available for hire
Hire TomTom Kre Sal
Verified Expert in Engineering
Machine Learning Engineer and Developer
Location
Rosice, South Moravian Region, Czech Republic
Toptal Member Since
June 29, 2021
Tom is a full-stack machine learning engineer with several years of experience in machine learning and software engineering, working on projects driven by smart algorithms and data. Tom gets a kick out of creating solutions to complex problems that positively impact the lives of others. Tom likes to keep abreast of cutting-edge technologies, which he then applies to production-ready systems—giving his clients an advantage over their competitors.
Portfolio
Sanad Cash, Inc
Data Science, Python, Data Extraction, Machine Learning, Azure Machine Learning...
StructionSite, Inc.
Computer Vision, Computer Vision Algorithms, Python, C++, Machine Vision...
Freelance
Agile, Azure, Artificial Intelligence (AI), Back-end, RabbitMQ, Kubernetes...
Experience
Availability
Part-time
Preferred Environment
Artificial Intelligence (AI), Computer Vision, Machine Learning, Back-end, Python, Linux, Cloud, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), GPT, Data Science
The most amazing...
... thing is to imagine something that does not exist and then try to build it.
Work Experience
Data Scientist/Data Engineer | Receipts Data Extraction Application
2022 - PRESENT
Sanad Cash, Inc
- Designed and implemented a machine learning system that recognizes and extracts meaningful information from accounting documents using deep learning algorithms.
- Designed and implemented highly scalable, reliable, and distributed back-end services using Python, FastAPI, Celery, Redis, and MongoDB to process incoming data in real-time.
- Implemented the detection and classification of important objects on input documents, like QR codes, tables, headings, company logos, signatures, and many more.
Technologies: Data Science, Python, Data Extraction, Machine Learning, Azure Machine Learning, Amazon Machine Learning, Google Cloud Machine Learning, Data Engineering, Architecture, Google Cloud AI, Azure Cosmos DB, Azure Cognitive Services, Vertex, Vertex AI, SpaCy, Hugging Face, DVC, Data Versioning, MLEM, Google Vision API, Handwriting Recognition, AWS Lambda, Amazon S3 (AWS S3), Amazon Textract, ChatGPT, Artificial Intelligence (AI)
Computer Vision Developer
2021 - 2022
StructionSite, Inc.
- Architected and built a pipeline to intelligently extract 3D-scene data from sequences of panoramic images, using a mix of geometric and deep learning approaches.
- Created custom neural network architectures for object detection, semantic, and instance segmentation designed to detect different construction-specific objects and their changes over time.
- Implemented the detection and anonymization of human faces and bodies on input video feeds for privacy reasons.
- Reconstructed the visual SLAM algorithm's walking trajectory from the input video feed to properly align the projected path on the floor plan, including important features (like walls, rooms, doors, windows, etc.) on building drawings.
- Managed the complete lifecycle of ML experiments (labels management, experiments tracking, evaluation, and deployments) with third-party tools like Google Vertex AI, Weights & Biases, Amazon SageMaker, or Metaflow (an open source project).
Technologies: Computer Vision, Computer Vision Algorithms, Python, C++, Machine Vision, Deep Learning, Machine Learning, Artificial Intelligence (AI), Machine Learning Operations (MLOps), Architecture, Hardware, Google Cloud AI, Real-time Data, Vertex, Vertex AI, Metaflow, Data Versioning, Google Vision API, AWS Lambda, Amazon S3 (AWS S3), Amazon Textract, Amazon SageMaker
Lead Full-stack Machine Learning Engineer
2020 - 2021
Freelance
- Developed a solution to extract meaningful information from invoices based on computer vision, natural language processing, and machine learning in general.
- Trained a conditional random field model on named entity recognition to classify important invoice fields.
- Created a solution to extract text from invoice images with a custom optical character recognition system based on deep learning.
- Designed the solution to be a highly scalable, robust system with many microservices running on top of a Kubernetes cluster.
- Created a mobile application that can analyze positioning, pricing, and out-of-stock goods, relying only on the photo of the product, and works with all types of packaging and product placement called Shelf Inspector.
Technologies: Agile, Azure, Artificial Intelligence (AI), Back-end, RabbitMQ, Kubernetes, Azure Kubernetes Service (AKS), Helm, Continuous Delivery (CD), Continuous Integration (CI), Machine Learning Operations (MLOps), PyTorch, Python, REST, GraphQL, Flask, Sanic Web Server, Fast.ai, PyTorch Lightning, Convolutional Neural Networks, Deep Learning, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Named-entity Recognition (NER), OCR, Git, MySQL, TensorBoard, Data Science, Data Visualization, Image Recognition, Microservices, Containers, Containerization, CI/CD Pipelines, GitLab CI/CD, GitHub, Data Modeling, Databases, Database Modeling, Predictive Modeling, Predictive Analytics, Data Pipelines, ETL, APIs, Test-driven Development (TDD), Performance Tuning, Performance Testing, Data Engineering, SQLAlchemy, Databricks, Svelte, Full-stack, DevOps, Pytest, SQL, Linux, Docker, Docker Compose, Jupyter Notebook, Bootstrap, Scrum, Kanban, Leadership, Cloud, React, JavaScript, Prometheus, Web Security, Web App Security, NGINX, Computer Vision Algorithms, XGBoost, Amazon Web Services (AWS), Data Analysis, Data Analytics, Machine Vision, PySpark, Spark ML, AI Design, Neptune, MLflow, Weights & Biases, Build Pipelines, Continuous Development (CD), GitHub Actions, Object Detection, Image Processing, Tesseract, Pytesseract, Image Analysis, Image Annotation, Data Extraction, Azure Machine Learning, ML Pipelines, Google Cloud, Object Tracking, Deep Neural Networks, Open Neural Network Exchange (ONNX), Metabase, Metaflow, Google Cloud Machine Learning, DocTR, Web Development, Natural Language Toolkit (NLTK), REST APIs, Google Cloud Platform (GCP), Keras, Python 3, Architecture, Azure Cognitive Services, Hugging Face, Data Versioning, Google Vision API, Handwriting Recognition, AWS Lambda, Amazon S3 (AWS S3), Amazon Textract, Amazon SageMaker
Senior Full-stack Machine Learning Engineer | CTO
2020 - 2021
Expansion of Eternity AG
- Developed an end-to-end solution to simulate a treatment's facial aesthetical impact.
- Trained Mask R-CNN models to detect possible treatment areas and advise on areas where doctors should focus.
- Developed a complete back-end solution consisting of REST API for a front-end application and a payment gateway, using a PostgreSQL database for storage.
- Implemented a precise detection of the face on the taken image and accurate detection of facial features like nose, eyes, mouth, etc.
- Detected the location of points on the face with very high accuracy for the injection of a substance for aesthetical treatment.
Technologies: PyTorch, Agile, Azure, Python, TensorFlow, Computer Vision, Scikit-learn, Scikit-image, NumPy, GPU Computing, Expo, Back-end, Machine Learning, Machine Learning Operations (MLOps), Artificial Intelligence (AI), Generative Adversarial Networks (GANs), Convolutional Neural Networks, Neural Networks, Docker, FastAPI, Fast.ai, Git, MySQL, TensorBoard, Data Science, Data Visualization, Image Recognition, Facial Recognition, Facial Tracking, Microservices, Containers, Containerization, CI/CD Pipelines, GitHub, Data Modeling, Databases, Database Modeling, Predictive Modeling, Predictive Analytics, Data Pipelines, ETL, APIs, Test-driven Development (TDD), Performance Tuning, Performance Testing, Data Engineering, SQLAlchemy, Databricks, Svelte, Full-stack, Node.js, DevOps, IceVision, Pytest, SQL, Linux, Docker Compose, Jupyter Notebook, Bootstrap, Scrum, Kanban, Leadership, Cloud, React, JavaScript, Web Security, Web App Security, NGINX, Computer Vision Algorithms, Deep Learning, Amazon Web Services (AWS), Data Analysis, Data Analytics, Machine Vision, AI Design, Neptune, MLflow, Weights & Biases, Build Pipelines, Continuous Development (CD), GitHub Actions, Object Detection, Image Processing, Image Analysis, Biometrics, Health, Image Annotation, Data Extraction, Azure Machine Learning, ML Pipelines, Object Tracking, Deep Neural Networks, Open Neural Network Exchange (ONNX), Metaflow, Google Cloud Machine Learning, Web Development, Natural Language Toolkit (NLTK), REST APIs, Google Cloud Platform (GCP), Google Cloud, Keras, Python 3, Architecture, Google Cloud AI, Real-time Data, Azure Cosmos DB, Azure Cognitive Services, Data Versioning, Google Vision API, AWS Lambda, Amazon S3 (AWS S3), Amazon Textract, Amazon SageMaker
Senior Full-stack Machine Learning Engineer | Co-founder
2017 - 2020
Industrial Vision
- Developed computer vision algorithms to detect defectively manufactured parts with high accuracy. It requires precise object detection and recognition algorithms that distinguish the most minor object characteristics.
- Implemented the notification of safety hazards. An area with robots requires specific safety rules: wearing a hard hat, glasses, and sometimes gloves. Implemented a solution to check all safety rules are followed from the feeds of security cameras.
- Created algorithms to navigate industrial robots using the robot operating system from a video feed. Detected obstacles and other objects to avoid robots crashing.
- Designed the whole product architecture from scratch as CTO of the company.
Technologies: Robot Operating System (ROS), Computer Vision, GPU Computing, Robotics, Amazon Web Services (AWS), Artificial Intelligence (AI), Docker, Python, PyTorch, TensorFlow, Computer Vision Algorithms, Machine Learning, RabbitMQ, Docker Swarm, Docker Compose, Linux, MongoDB, PostgreSQL, Scikit-learn, Scikit-image, NumPy, Pandas, Grafana, Ansible, Git, MySQL, TensorBoard, Data Science, Data Visualization, Image Recognition, Facial Recognition, Facial Tracking, Microservices, Containers, Containerization, CI/CD Pipelines, GitLab CI/CD, GitHub, Data Modeling, Databases, Database Modeling, Predictive Modeling, Predictive Analytics, Data Pipelines, ETL, APIs, Test-driven Development (TDD), Performance Tuning, Performance Testing, Data Engineering, SQLAlchemy, Full-stack, Node.js, DevOps, Pytest, SQL, Jupyter Notebook, Bootstrap, Scrum, Kanban, Leadership, Cloud, React, JavaScript, Prometheus, GraphQL, Redis, Web Security, Web App Security, NGINX, Memcached, Convolutional Neural Networks, Deep Learning, Data Analysis, Data Analytics, Machine Vision, AI Design, MLflow, Build Pipelines, Continuous Development (CD), Object Detection, Image Processing, Image Analysis, Image Annotation, Amazon Machine Learning, ML Pipelines, Object Tracking, Deep Neural Networks, Web Development, Natural Language Toolkit (NLTK), REST APIs, Keras, Python 3, Architecture, Hardware, CCTV, Real-time Data, Data Versioning, AWS Lambda, Amazon S3 (AWS S3)
Head of Development, Search Engine
2014 - 2017
Seznam.cz
- Redesigned the architecture and generated technical solutions for our full-text core technology, which enabled the widespread adoption of our solution across the whole company in multiple projects.
- Spearheaded a modernization of the development process by establishing the brand-new roles of DevOps and SRE, which resulted in a faster process of releasing the changes into production.
- Delivered new functionalities such as an image search engine which was astoundingly successful in the highly competitive market of search engines in Central Europe.
Technologies: Leadership, Management, Agile, Scrum, IT Project Management, IT Product Management, Artificial Intelligence (AI), Big Data, Software Architecture, Git, MySQL, Containers, Containerization, CI/CD Pipelines, GitLab CI/CD, GitHub, Data Modeling, Databases, Database Modeling, Predictive Analytics, Data Pipelines, ETL, APIs, Test-driven Development (TDD), Performance Tuning, Performance Testing, Apache Kafka, Data Engineering, Full-stack, DevOps, SQL, Linux, Python, Docker, Jupyter Notebook, Bootstrap, Kanban, Cloud, Web Security, Web App Security, NGINX, Amazon Web Services (AWS), PySpark, AI Design, Build Pipelines, Continuous Development (CD), Object Detection, Image Processing, Image Analysis, Image Annotation, Deep Neural Networks, Web Development, REST APIs, Python 3, Architecture, Real-time Data, AWS Lambda, Amazon S3 (AWS S3)
Senior Back-end Developer
2011 - 2015
Seznam.cz
- Developed an internal system for objective quality measurement of the full-text search system. It allowed product managers to focus on important features with the most benefit for the end-users.
- Scaled the core of the full-text engine to processing a triple amount of data.
- Redesigned the architecture of the system for taking screenshots of internet pages on a scale of thousands of pages per second.
Technologies: Python, Continuous Delivery (CD), Continuous Integration (CI), Grafana, Prometheus, Docker, Kubernetes, PostgreSQL, MongoDB, Flask, JavaScript, Back-end, React, Spark, Hadoop, Big Data, Software Architecture, Bootstrap, Elasticsearch, Redis, Memcached, Git, MySQL, Microservices, Containers, Containerization, CI/CD Pipelines, GitLab CI/CD, GitHub, Data Modeling, Databases, Database Modeling, Data Pipelines, ETL, APIs, Test-driven Development (TDD), Performance Tuning, Performance Testing, Apache Kafka, Data Engineering, SQLAlchemy, Full-stack, Node.js, Pytest, SQL, Linux, Jupyter Notebook, C++, Scrum, Kanban, GraphQL, Web Security, Web App Security, NGINX, Build Pipelines, Image Annotation, Web Development, REST APIs, Python 3
Experience
Visiobelle
http://www.visiobelle.comA computer vision-based mobile application that helps doctors and their patients view the final results of a planned medical procedure.
In a small team of three members, I was the lead machine learning engineer and back-end developer in the build of this app. Due to the nature of the application, we paid particular focus on generating trustful results while maintaining high-security standards.
In a small team of three members, I was the lead machine learning engineer and back-end developer in the build of this app. Due to the nature of the application, we paid particular focus on generating trustful results while maintaining high-security standards.
Seznam.cz Full-text Search Engine
https://search.seznam.cz/A Czech-based full-text search engine by Seznam.cz that answers user questions with information ingeniously found on the internet and presented inventively.
I started this project at the beginning of my career, and I participated in developing this search engine as a back-end developer within a large team. A few years later, I became head of the development of the whole full-text platform. This was when I became increasingly passionate about algorithms driven by data and machine learning, and after that, I decided to start my own business.
I started this project at the beginning of my career, and I participated in developing this search engine as a back-end developer within a large team. A few years later, I became head of the development of the whole full-text platform. This was when I became increasingly passionate about algorithms driven by data and machine learning, and after that, I decided to start my own business.
Robotic System Air Hockey Game
https://fb.watch/6kAEW9qBGv/Industrial Vision was a project focused on advanced automation and robotics in the automotive industry and the main purpose of the system was to detect defectively manufactured parts.
I was a lead machine learning engineer, and I was responsible for creating the algorithms from the proof of concept to production-ready systems.
To demonstrate our ability, we created a robotic system that can play an air hockey game against a human player. The game was publicly announced in a trade fair called Amper in 2019. You can still see the video at the link below.
• https://fb.watch/6kAEW9qBGv/
It was a real-time computer vision system with multiple object detection while. being able to control and navigate with the robotic 6-axis arm.
I was a lead machine learning engineer, and I was responsible for creating the algorithms from the proof of concept to production-ready systems.
To demonstrate our ability, we created a robotic system that can play an air hockey game against a human player. The game was publicly announced in a trade fair called Amper in 2019. You can still see the video at the link below.
• https://fb.watch/6kAEW9qBGv/
It was a real-time computer vision system with multiple object detection while. being able to control and navigate with the robotic 6-axis arm.
Extracting Information from Invoices
A system for extracting meaningful information from invoices that's based on machine learning, computer vision, and natural language processing.
I worked on this project as the lead machine learning engineer and responsible for designing solutions from scratch to production.
The solution is divided into three major stages. In the first stage, we standardized the format of incoming invoices. It includes some computer vision tasks and classification models based on convolution neural networks. In the next stage, we implemented optical character recognition for extracting raw text from invoices. The last step consists of named entity recognition and some post-processing for the final classification of important information on the invoice.
We also used production algorithms in highly scalable microservices running in a Kubernetes cluster that communicated over a RabbitMQ message broker.
I worked on this project as the lead machine learning engineer and responsible for designing solutions from scratch to production.
The solution is divided into three major stages. In the first stage, we standardized the format of incoming invoices. It includes some computer vision tasks and classification models based on convolution neural networks. In the next stage, we implemented optical character recognition for extracting raw text from invoices. The last step consists of named entity recognition and some post-processing for the final classification of important information on the invoice.
We also used production algorithms in highly scalable microservices running in a Kubernetes cluster that communicated over a RabbitMQ message broker.
Shelf Inspector
Shelf Inspector is a mobile app and a powerful tool for merchandisers, sales reps, and managers. It analyzes positioning, out-of-stock merchandise, pricing, and more—from a simple photo of a shelf in the store, and it works with all kinds of packaging and placement. The project comprises precise and robust object detection and location in different shapes and lighting conditions.
Skills
Languages
Python, Python 3, SQL, JavaScript, GraphQL, C++
Frameworks
Flask, Bootstrap, Spark, Svelte, Hadoop
Libraries/APIs
Fast.ai, PyTorch Lightning, REST APIs, Keras, PyTorch, TensorFlow, Scikit-learn, OpenCV, SQLAlchemy, React, Pandas, NumPy, Node.js, Flask-RESTful, XGBoost, PySpark, Spark ML, Natural Language Toolkit (NLTK), Azure Cognitive Services, SpaCy, Google Vision API
Tools
Docker Compose, Git, RabbitMQ, NGINX, GitHub, Scikit-image, Grafana, Pytest, Helm, Ansible, Docker Swarm, Expo, TensorBoard, Azure Kubernetes Service (AKS), Named-entity Recognition (NER), GitLab CI/CD, Azure Machine Learning, Google Cloud AI, Amazon SageMaker
Paradigms
Data Science, REST, Continuous Integration (CI), Test-driven Development (TDD), Continuous Development (CD), Agile, Scrum, Kanban, Microservices, DevOps, Continuous Delivery (CD), Management, ETL
Platforms
Linux, Docker, Jupyter Notebook, Azure, AWS Lambda, Kubernetes, Databricks, Amazon Web Services (AWS), Google Cloud Platform (GCP), Apache Kafka
Storage
Amazon S3 (AWS S3), PostgreSQL, MongoDB, MySQL, Redis, Elasticsearch, Memcached, Databases, Database Modeling, Data Pipelines, Google Cloud, Azure Cosmos DB
Other
Artificial Intelligence (AI), Computer Vision, Neural Networks, Machine Learning, Data Engineering, Cloud, Full-stack, Machine Learning Operations (MLOps), IceVision, Software Architecture, Back-end, FastAPI, OCR, Computer Vision Algorithms, Convolutional Neural Networks, Sanic Web Server, Deep Learning, Image Recognition, Facial Tracking, Containers, Containerization, CI/CD Pipelines, APIs, Machine Vision, AI Design, Build Pipelines, GitHub Actions, Object Detection, Image Processing, Tesseract, Pytesseract, Deep Neural Networks, Image Analysis, Image Annotation, Data Extraction, Architecture, Real-time Data, Amazon Textract, Leadership, Big Data, Prometheus, Generative Adversarial Networks (GANs), Natural Language Processing (NLP), Web Security, IT Project Management, IT Product Management, Web App Security, Data Visualization, Facial Recognition, Data Modeling, Predictive Modeling, Predictive Analytics, Performance Tuning, Performance Testing, Data Analysis, Data Analytics, Algorithms, Neptune, MLflow, Weights & Biases, Metabase, Open Neural Network Exchange (ONNX), Biometrics, Health, Amazon Machine Learning, Google Cloud Machine Learning, ML Pipelines, Object Tracking, DocTR, Web Development, Hardware, CCTV, ChatGPT, Generative Pre-trained Transformer 3 (GPT-3), Vertex, Vertex AI, Hugging Face, GPT, Generative Pre-trained Transformers (GPT), DVC, Data Versioning, MLEM, Handwriting Recognition, Robot Operating System (ROS), GPU Computing, Robotics, ABB Robots, Metaflow
Education
2008 - 2011
Bachelor's Degree in Information Technology
Brno University of Technology Faculty of Information Technology - Brno, Czech Republic