Oleksandr S.
Computer Vision Engineer
Alexander specializes in the development and deployment of high-load Artificial Intelligence systems, with a particular focus on Computer Vision and MLOps infrastructure. His expertise spans the entire product lifecycle: from processing terabytes of raw data and field-calibrating sensors to deploying scalable microservices in Kubernetes. He excels at transforming complex technological challenges - whether defending against synthetic deepfakes or automating industrial agriculture - into stable, production-ready solutions. With a deep background in Computer Vision, Alexander has successfully developed systems for robotic yield estimation using 3D cameras, SLAM, and satellite imagery analysis. Rather than simply training models, he builds a robust MLOps foundation around them - leveraging automated pipelines in Airflow and ClearML to inference optimization via ONNX. This approach ensures high predictive accuracy and metric transparency throughout every stage of the system’s operation.
Key Expertise
Experience
9+ years
Timezone
CET (GMT +1)
1. Fruit Counting System for Agricultural Robotics
Project overview:
Farmers and agri-tech companies required automated fruit yield estimation to plan harvest and optimize logistics. Designed a robotic vision system to count oranges on trees using 3D cameras, depth sensors, and GPS.
Responsibilities:
- Calibrated 3D cameras in the field and developed a depth-aware detection model to estimate fruit per tree.
- Combined data with drone and satellite imagery for full orchard analysis.
- Delivered a platform with dashboards showing yield distribution and tree health.
Achievements:
Enabled precise yield forecasting and reduced manual labor. The system helped farmers make data-driven harvesting decisions.
Key Expertise
Experience
9+ years
Timezone
CET (GMT +1)
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Computer Vision Engineer
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