Machine Learning Engineer (part-time contract)
Traffic Technique
Keywords
Machine Learning
Artificial Neural Networks
Traffic Flow
Data Analysis
Computer Vision
Databases
Data Mining
Data Visualization
Python (Programming Language)
Object Detection
Skills
Machine Learning
Expertise in machine learning techniques, including deep learning and computer vision, with practical application in traffic flow optimization and autonomous driving.
Programming Languages
Proficiency in Python and various ML frameworks such as TensorFlow/Keras, Pandas, Scikit, PIL, OpenCV for developing and implementing machine learning solutions.
Data Analysis and Visualization
Skills in data mining, data visualization, and analysis, applied to real-time traffic data and signal processing projects.
Database Management
Knowledge of SQL for managing and querying databases in machine learning projects.
Version Control and Collaboration
Proficiency with Git and GitLab for code versioning and collaborative development.
API Development
Experience in deploying FastAPI services for real-time access to machine learning models.
Neural Network Architectures
Expertise in Convolutional Neural Networks (CNN) for autonomous driving and object detection applications.
Expertise in machine learning techniques, including deep learning and computer vision, with practical application in traffic flow optimization and autonomous driving.
Programming Languages
Proficiency in Python and various ML frameworks such as TensorFlow/Keras, Pandas, Scikit, PIL, OpenCV for developing and implementing machine learning solutions.
Data Analysis and Visualization
Skills in data mining, data visualization, and analysis, applied to real-time traffic data and signal processing projects.
Database Management
Knowledge of SQL for managing and querying databases in machine learning projects.
Version Control and Collaboration
Proficiency with Git and GitLab for code versioning and collaborative development.
API Development
Experience in deploying FastAPI services for real-time access to machine learning models.
Neural Network Architectures
Expertise in Convolutional Neural Networks (CNN) for autonomous driving and object detection applications.
Project history
12/2022
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Present
Implemented a real-time adaptive traffic light adjustment system, optimized traffic flow management solutions, and analyzed time series traffic data to predict and adjust traffic patterns in real-time.
03/2022
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Present
Research Associate | Machine Learning Engineer
Centre for Research & Technology Hellas (CERTH)
Deployed FastAPI services for real-time ML model access, led PVGnosis project for solar panel defect detection using drone imagery, presented research findings at conferences, and participated in Horizon projects.
09/2021
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11/2022
Thesis Research
DEMOCRITUS UNIVERSITY OF THRACE
Developed and implemented Convolutional Neural Networks (CNN) for Autonomous Driving, utilized computer vision techniques to classify traffic lights in real-time using CNNs, and proposed a method to calculate the distance of different objects.
Local Availability
Only available for remote work
