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Machine Learning Engineer with a background in Mechatronics, experienced in building reproducible ML pipelines across computer vision and NLP.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Fight-Detection-YOLO26-LSTM
February 27, 2026 – Present
Fight-Detection-YOLO26-LSTM — GitHub repository
View ProjectVehicle-License-Plate-Detection-with-YOLO26
February 27, 2026 – Present
Vehicle-License-Plate-Detection-with-YOLO26 — GitHub repository
View ProjectPDF_Summarizer_Gemini
February 2, 2026 – Present
PDF_Summarizer_Gemini — GitHub repository
View ProjectBilingual-RAG-Chatbot-for-International-Students
December 20, 2025 – Present
Bilingual-RAG-Chatbot-for-International-Students — GitHub repository
View ProjectOrganoid-Brightfield-to-Fluorescence-Image-Translation
August 3, 2025 – Present
Organoid-Brightfield-to-Fluorescence-Image-Translation — GitHub repository
View ProjectClassification-of-License-Plates-by-State
July 8, 2025 – August 3, 2025
Classification-of-License-Plates-by-State — GitHub repository
View ProjectSkin-Cancer-Classification-Bening_vs_Malignant
April 27, 2025 – May 22, 2025
Skin-Cancer-Classification-Bening_vs_Malignant — GitHub repository
View ProjectCultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest in applying machine learning to diverse problems, from computer vision to natural language processing. This breadth suggests adaptability and a curious mindset, which can be positive for cultural fit in an innovative environment. However, all projects are personal, and there is no information on team collaboration or professional experience, making a comprehensive cultural fit assessment challenging. The focus on practical applications aligns well with a data scientist role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise, primarily listing technologies and project names, which limits insight into collaboration or problem-solving approaches.