Kiril C.
Machine Learning Engineer
Kiril is a seasoned Computer Scientist with over a decade of experience across diverse industries such as political/election technology, gaming, supply chain management, remote sensing, proptech, and education.
His contributions include developing a scalable machine learning algorithm for satellite data analysis, significantly impacting urban planning and environmental monitoring.
Kiril's unique blend of technical prowess and creative passion underscores his commitment to excellence and continuous learning.
Hauptkompetenz
- Flask 4 Jahre
- PostgreSQL 5 Jahre
- Python 6 Jahre
Andere Fähigkeiten
- Kubernetes 5 Jahre
- ETL 3 Jahre
- Apache Airflow 3 Jahre
Ausgewählte Erfahrung
Beschäftigung
Senior Machine Learning Engineer
Resolute Asset Management - 4 jahre 2 monate
- Developed, trained, and deployed Deep Learning solutions on the Google Cloud platform.
- Developed and deployed big data processing pipelines to production.
- Developed ML models estimating asset quality from images, asset valuation from characteristics, and feature extraction from documents.
- Managed Google Cloud triggers and configurations for defining and utilizing CI/CD pipelines.
- Conducted interviews for Machine Learning / Data Science positions.
Technologien:
- Technologien:
ETL
Apache Airflow
Flask
PostgreSQL
Redis
Pandas
- NLP
- Computer Vision
SQLAlchemy
Google Cloud
OpenCV
Kubeflow
Dataflow
LangChain
Apache Spark
Kubernetes
Scikit-learn
- PyTorch
Docker
Machine Learning
- MLOps
Lecturer and Content Developer
Brinster Academy - 2 jahre
- Developed curriculum and content for courses in Machine Learning, Big Data, and Final Projects.
- Mentored and taught students diverse topics of Machine Learning and Big Data.
- Organized online webinars for Deep Learning and Machine Learning.
Technologien:
- Technologien:
Flask
Python
Pandas
- NLP
- Computer Vision
Hadoop
Apache Hive
OpenCV
Apache Spark
Scikit-learn
TensorFlow
Keras
Docker
Machine Learning
Machine Learning Engineer
Symphony.is - 1 jahr 10 monate
- Developed a computer vision model predicting house metrics based on large-scale satellite images.
- Developed Computer-Vision/NLP models with high accuracy for production.
- Integrated Machine Learning solutions to AWS Cloud Pipelines.
- Utilized SageMaker to build, train, and deploy machine learning models efficiently.
- Developed solution proposals for new clients.
- Conducted interviews for Machine Learning / Data Science positions.
Technologien:
- Technologien:
Flask
PostgreSQL
Redis
Python
Pandas
- NLP
- Computer Vision
AWS
OpenCV
Apache Spark
Kubernetes
Scikit-learn
TensorFlow
Keras
- PyTorch
Docker
Machine Learning
Ausbildung
MSc.Computer Science
Faculty of Computer Science and Engineering - Skopje · 2019 - 2024
BSc.Computer Science
Faculty of Computer Science and Engineering - Skopje · 2010 - 2014
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