Kujtim is available for hire
Hire KujtimKujtim Rahmani
Verified Expert in Engineering
Machine Learning Developer
Location
Kumanovo, Municipality of Kumanovo, Macedonia
Toptal Member Since
August 7, 2023
Kujtim is a computer vision and machine learning engineer with over ten years of experience and more than four years of experience in academia. During his tenure, he worked with four startups, where he built products from scratch. Furthermore, Kujtim also worked as a consultant for esteemed clients such as the German automotive industry and Heraeus Group and as a data scientist researcher for Airbus.
Portfolio
Jack Zerby Consulting, LLC
Artificial Intelligence (AI), Machine Learning, Computer Vision, Python...
Pano
Python, PyTorch, OpenCV, Machine Learning, Computer Vision...
Rare Edition
Python, Amazon Web Services (AWS), TensorFlow, Keras, Docker, SQL...
Experience
Availability
Part-time
Preferred Environment
Ubuntu, Windows, Visual Studio Code (VS Code)
The most amazing...
...thing I've developed is the SOTA algorithm for defect detection for airplane parts. I used traditional ML to build SOTA for segmentation in a small dataset.
Work Experience
AI/ML Expert and Consultant
2023 - PRESENT
Jack Zerby Consulting, LLC
- Created an algorithm for the intelligent processing of collectible images. Developed several supervised detection and intelligent character processing of collectibles. Handled several templates.
- Helped the team integrate the service in the AWS and contributed to designing the app.
- Fine-tuned several deep learning models to process and better recognize the text in the images, as well as handle the errors made by the recognizer.
Technologies: Artificial Intelligence (AI), Machine Learning, Computer Vision, Python, Image Recognition, Convolutional Neural Networks (CNN), OCR, Information Extraction, OpenCV, Deep Learning, Image Processing, Intelligent Character Recognition, Pytesseract, Tesseract, You Only Look Once (YOLO), Data Structures, Object Detection
Senior Data Scientist | Computer Vision
2023 - PRESENT
Pano
- Built computer vision algorithms for fire detection and tracking in forests.
- Developed mathematical modeling of the fire initiation and growth during the night. Used Python, OpenCV, scikit-learn, GCP, and GitHub.
- Created a tracking algorithm for tracking forest fires during the night.
Technologies: Python, PyTorch, OpenCV, Machine Learning, Computer Vision, Artificial Intelligence (AI), Data Science, Matplotlib, Deep Learning, Image Processing, Algorithms, Object Tracking, Object Detection, You Only Look Once (YOLO), Probability Theory, Statistics, Convolutional Neural Networks (CNN), Loss Modeling, NumPy, Computer Vision Algorithms, Visualization, Video Processing, Neural Networks, Startups, Data Structures
Senior Computer Vision Engineer
2021 - PRESENT
Rare Edition
- Built computer vision algorithms for card and coin defect evaluation. Conducted quality assurance for collectibles.
- Communicated with operations (graders), back-end services, and the mobile developer to ensure all computer vision algorithms ran correctly.
- Created an active learning platform for card grading.
Technologies: Python, Amazon Web Services (AWS), TensorFlow, Keras, Docker, SQL, Machine Learning, Computer Vision, Artificial Intelligence (AI), Data Analysis, Amazon S3 (AWS S3), Matplotlib, Deep Learning, Image Processing, Algorithms, Linear Regression, PostgreSQL, Object Detection, Pandas, You Only Look Once (YOLO), Image Recognition, Probability Theory, Statistics, PySQL, Convolutional Neural Networks (CNN), Data Analytics, NumPy, Computer Vision Algorithms, Data Structures, Database Design, Databases, Visualization, Labeling, Neural Networks, Startups, Intelligent Character Recognition, Information Extraction, Dynamic Programming, OpenCV, Defect Detection
Machine Learning Engineer
2023 - 2023
CollX
- Developed an image search and matching engine for sports like baseball, basketball, and soccer and game cards such as Pokemon and Magic. The users can take a photo of their card, and my algorithm finds the matching card in the system.
- Used contrastive and triplet loss metrics to build an image embedding system.
- Created a hard example mining system for algorithm improvement.
- Built a Faiss indexer to index the card images and integrated feature matching to filter the best results.
Technologies: PyTorch, FAISS, OpenCV, Open Neural Network Exchange (ONNX), Flask, Pandas, Machine Learning, Computer Vision, Artificial Intelligence (AI), Data Analysis, Matplotlib, Deep Learning, Image Processing, Data Engineering, Algorithms, PostgreSQL, Image Search, Image Recognition, Probability Theory, Statistics, Convolutional Neural Networks (CNN), Loss Modeling, Data Analytics, NumPy, Databases, Visualization, Labeling, Neural Networks, Startups, Intelligent Character Recognition, Information Extraction, Python
Senior Data Scientist | Computer Vision
2023 - 2023
Ramani
- Built computer vision algorithms for object detection, counting, and tracking in warehouses.
- Conducted 3D reconstruction of the objects based on multiple images.
- Managed junior computer vision engineers and annotators.
Technologies: PyTorch, Python, OpenCV, Scikit-learn, Amazon Web Services (AWS), Graph Theory, Machine Learning, Computer Vision, Artificial Intelligence (AI), Data Science, Matplotlib, Deep Learning, Image Processing, Data Engineering, 3D Image Processing, 3D Reconstruction, Object Detection, Flask, Probability Theory, Statistics, Convolutional Neural Networks (CNN), Open Neural Network Exchange (ONNX), NumPy, Computer Vision Algorithms, Data Structures, Visualization, Labeling, Neural Networks, Startups, Dynamic Programming, Intelligent Character Recognition, Pytesseract, OCR, You Only Look Once (YOLO)
Senior Data Scientist | Computer Vision
2023 - 2023
Smartauger
- Built computer vision algorithms for objects like pipes and optical fiber cables and their detection in electromagnetic wave-generated images from ground-penetrating radars.
- Ran experiments and built the algorithm using simulated and real data.
- Guided the stakeholders on how to acquire the data from real scenarios.
Technologies: PyTorch, Computer Vision, Amazon Web Services (AWS), Scikit-learn, Object Detection, Machine Learning, Artificial Intelligence (AI), Data Analysis, Amazon S3 (AWS S3), Matplotlib, Deep Learning, You Only Look Once (YOLO), Probability Theory, Statistics, Convolutional Neural Networks (CNN), Data Analytics, NumPy, Computer Vision Algorithms, Labeling, Neural Networks, Startups, OpenCV, Image Processing, Tesseract, Defect Detection
Senior Data Scientist | Computer Vision
2022 - 2023
Heraeus
- Built computer vision algorithms for object detection and tracking of defects of manufactured parts in X-ray images.
- Optimized the detection and tracking to process more than 17 images per second.
- Collaborated with the clients to ensure the data and annotation were of the best quality.
Technologies: Python, PyTorch, OpenCV, Open Neural Network Exchange (ONNX), You Only Look Once (YOLO), Kalman Filtering, Scikit-learn, Random Forests, Pandas, Machine Learning, Computer Vision, Artificial Intelligence (AI), Data Science, Azure, Matplotlib, Deep Learning, Image Processing, Decision Trees, Data Engineering, Algorithms, Object Tracking, Object Detection, Probability Theory, Statistics, Convolutional Neural Networks (CNN), NumPy, Computer Vision Algorithms, Visualization, Video Processing, Labeling, Neural Networks, Defect Detection
Machine Learning Engineer
2022 - 2022
Tolstoy
- Built an OCR automatic parsing of the electricity bills.
- Integrated Google Drive with the Cloud Run and Cloud Scheduler to ensure new data was parsed after being uploaded to Google Drive.
- Handled several electricity bill templates and file formats.
Technologies: Tesseract, Pytesseract, OCR, Docker, Google Cloud Platform (GCP), Pandas, Flask, Machine Learning, Artificial Intelligence (AI), Data Analysis, Data Engineering, Probability Theory, Statistics, NumPy, Databases, Startups, Intelligent Character Recognition, Information Extraction, OpenCV, Python
Data Scientist Consultant
2019 - 2021
Cluster Reply
- Built an object detection and tracking algorithm for counting objects in 3D computed tomography images of vehicle parts. Reduced the time from around 120 minutes to five minutes.
- Created an invoice data extraction algorithm for a private German digital post service.
- Developed NLP algorithms for a research paper, understanding and computing its correlation to each of the UN countries' sustainable development goals.
- Prepared machine learning and data science project proposals for customers.
Technologies: Python, OpenCV, Keras, TensorFlow, Azure Cognitive Services, Scikit-learn, Kalman Filtering, Machine Learning, Computer Vision, Artificial Intelligence (AI), Data Science, Data Analysis, Azure, Matplotlib, Scikit-image, Deep Learning, Image Processing, Decision Trees, Data Engineering, Random Forests, Algorithms, Linear Regression, Object Tracking, 3D Image Processing, Object Detection, Deep Sorting, Probability Theory, Statistics, PySQL, Convolutional Neural Networks (CNN), Data Analytics, NumPy, Computer Vision Algorithms, Data Structures, Databases, Visualization, Video Processing, Labeling, Neural Networks, Intelligent Character Recognition, Information Extraction, Dynamic Programming, Pytesseract, You Only Look Once (YOLO), Defect Detection
Data Scientist
2018 - 2019
Airbus
- Built a pore detection algorithm in 3D CT scans of airplane parts with 99.9% accuracy.
- Created a system design for change detection in airplane cabins using radio frequency signals.
- Guided the material scientist on data annotation and understanding how ML algorithms work.
Technologies: Python, TensorFlow, Scikit-learn, Amazon Web Services (AWS), Machine Learning, Computer Vision, Artificial Intelligence (AI), Data Science, Amazon S3 (AWS S3), Matplotlib, Image Processing, Algorithms, Linear Regression, 3D Image Processing, SVMs, Probability Theory, Statistics, Data Analytics, NumPy, Computer Vision Algorithms, Research, Visualization, Labeling, Neural Networks, OpenCV, Object Detection, Defect Detection
Research Assistant and Scientist
2015 - 2018
UniBW
- Developed a semantic scene segmentation algorithm for facade images, which is state of the art for small datasets.
- Created a dataset for detailed facade segmentation, including transom and mullion windows. Analyzed and considered data for creating high-quality 3D building models.
- Built a complete pipeline for facade segmentation from data acquisition up to deployment.
Technologies: C++, OpenCV, TensorFlow, Keras, Machine Learning, Computer Vision, Artificial Intelligence (AI), Data Science, Matplotlib, Deep Learning, Decision Trees, Data Engineering, Random Forests, Algorithms, Object Detection, Number Theory, Probability Theory, Statistics, Convolutional Neural Networks (CNN), Loss Modeling, Data Analytics, NumPy, Computer Vision Algorithms, Research, Data Structures, Visualization, Labeling, Neural Networks, Dynamic Programming, Image Processing, Python
Machine Learning Engineer
2014 - 2015
Zyncd
- Built a matching algorithm to match user profiles with problem descriptions.
- Improved the accuracy of the matching by more than 50%.
- Developed a ranking algorithm using mathematical functions to normalize profiles.
- Integrated word2vec into the system for profile embedding.
Technologies: Python, Scikit-learn, CherryPy, Machine Learning, Artificial Intelligence (AI), Data Science, Data Engineering, Algorithms, Probability Theory, Statistics, Data Analytics, NumPy, Database Design, Databases, Neural Networks, Startups, Information Extraction, Dynamic Programming, Deep Learning
Computer Lab Teacher
2011 - 2012
Ss. Cyril and Methodius University in Skopje
- Held calculus courses for first and third-year students.
- Conducted discrete mathematics courses for first-year students.
- Taught a course on the basics of IT for first-year students.
Technologies: Mathematics, Algorithms, Number Theory, Statistics, Probability Theory, Dynamic Programming
Experience
Image-searching Engine for Cards
http://collx.appDeveloped an image-matching algorithm for searching cards. The database contains millions of images. The user can take a photo, and the algorithm will find the cards that are the same as the photo and show the cards and additional information about them to the user.
Pore Detection Algorithm in 3D CT Scans
A pore detection algorithm in 3D CT scans of airplane parts with 99.9% accuracy. I built the algorithm using several Gaussian modifications and transformed data to an n-modal normal distribution. Furthermore, I made high-quality decision boundaries between all n distributions and classified each region on one of these distributions. Also, I worked on simulating the data.
Object Detection in 3D-computed Tomography Images
An object detection and tracking algorithm that I built for counting objects in 3D CT images of vehicle parts. Reduced the human (worker) time from around 120 minutes to 5 minutes.
Each CT image was around 1GB. Since there was no pre-trained model for 3D images, I converted the problem to object detection in each slice of the 3D image and then used tracking and dynamic programming to recreate and delineate the 3D objects.
Each CT image was around 1GB. Since there was no pre-trained model for 3D images, I converted the problem to object detection in each slice of the 3D image and then used tracking and dynamic programming to recreate and delineate the 3D objects.
Semantic Scene Segmentation Algorithm for Façade Images
https://isprs-annals.copernicus.org/articles/IV-2/223/2018/isprs-annals-IV-2-223-2018.pdfA semantic segmentation pipeline that I built for façades. This is a hybrid pipeline consisting of traditional machine learning algorithms (the structured random forest model), an iterative optimization technique, a deep learning region proposal network, and a dynamic programming optimization technique based on the façade object constraints.
Information Extraction from Collectibles
I built information extraction, character recognition, and information structuring algorithms for collectibles. My role was to make the brain (AI) of the application. Furthermore, I was constantly communicating with the developers and the stakeholders since I was the person who knew both the market and the technology.
Education
2016 - 2019
PhD in Artificial Intelligence
University of the Bundeswehr Munich - Munich, Germany
2012 - 2014
Master's Degree in Computer Science
Technical University of Munich - Munich, Germany
2008 - 2012
Bachelor's Degree in Computer Science
Ss. Cyril and Methodius University in Skopje - Skopje, Macedonia
Certifications
MARCH 2024 - PRESENT
Certified Microsoft Trainer
Microsoft
MARCH 2024 - MARCH 2025
Azure AI Associate
Microsoft
JANUARY 2024 - PRESENT
CertNexus Certified Artificial Intelligence Practitioner (CAIP)
CertNexus
JANUARY 2024 - JANUARY 2027
CertNexus Certified Artificial Intelligence Practitioner (CAIP)
CertNexus
OCTOBER 2020 - OCTOBER 2024
Microsoft Certified: Azure Data Scientist Associate
Microsoft
Skills
Libraries/APIs
OpenCV, NumPy, TensorFlow, Keras, PyTorch, Scikit-learn, Matplotlib, Pandas, Azure Cognitive Services
Tools
You Only Look Once (YOLO), Scikit-image, IPython Notebook, ChatGPT
Languages
Python, C++, SQL
Paradigms
Data Science, Dynamic Programming, Database Design
Industry Expertise
Teaching
Platforms
Amazon Web Services (AWS), Azure, Docker, Google Cloud Platform (GCP)
Storage
Amazon S3 (AWS S3), PostgreSQL, Databases
Frameworks
Flask, CherryPy
Other
Machine Learning, Deep Learning, Computer Vision, Image Processing, Random Forests, Mathematics, Algorithms, Data Structures, Object Detection, Artificial Intelligence (AI), Data Analysis, Decision Trees, Probability Theory, Statistics, Convolutional Neural Networks (CNN), Data Analytics, Computer Vision Algorithms, Research, Labeling, Neural Networks, Startups, Intelligent Character Recognition, Defect Detection, Natural Language Processing (NLP), Kalman Filtering, OCR, Tesseract, Data Engineering, Linear Regression, Object Tracking, 3D Image Processing, Image Search, Number Theory, PySQL, Loss Modeling, Open Neural Network Exchange (ONNX), Visualization, Video Processing, Information Extraction, Graph Theory, FAISS, Pytesseract, 3D Reconstruction, SVMs, Deep Sorting, Image Recognition, Statistical Methods, Statistical Modeling, OpenAI, Training
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