Dawit Fentie

Key Skills

Software

CVAT

Top Subject Matter

No subject matter listed

Top Data Types

Video

Top Label Types

Bounding Box

Entity Ner Classification

Segmentation

Freelancer Overview

I am a Principal AI & Machine Learning Engineer with extensive experience building end-to-end AI and analytics systems, including data collection, labeling, and annotation workflows essential for high-quality model training. My background spans NLP, recommendation engines, and advanced forecasting, where I have designed scalable data pipelines, implemented rigorous data validation processes, and established data governance standards to ensure the accuracy and reliability of training datasets. I am highly skilled in Python, SQL, MLflow, DVC, and cloud deployment, and have led cross-functional teams to translate complex business needs into actionable, data-driven solutions. My work has included architecting sentiment-driven analytics platforms, developing enterprise forecasting models, and mentoring teams on best practices in data preparation and annotation for AI projects.

Labeling Experience

identifying objects in autonomous vehicle

CVATVideoBounding BoxEntity Ner Classification

1. Computer Vision (Image/Video Labeling) Bounding Boxes (Object Detection): Drawing rectangles around objects in images, such as cars, pedestrians, and traffic lights for autonomous vehicle AI. Polygon Annotation (Segmentation): Precisely outlining the edges of objects, such as identifying specific tumor shapes in X-ray images. Key-Point Annotation: Marking specific points on an image, such as joints on a human body for gesture recognition. Image Classification/Tagging: Categorizing an entire image based on content (e.g., "contains a cat," "indoor scene," "high quality" vs. "low quality").

1. Computer Vision (Image/Video Labeling) Bounding Boxes (Object Detection): Drawing rectangles around objects in images, such as cars, pedestrians, and traffic lights for autonomous vehicle AI. Polygon Annotation (Segmentation): Precisely outlining the edges of objects, such as identifying specific tumor shapes in X-ray images. Key-Point Annotation: Marking specific points on an image, such as joints on a human body for gesture recognition. Image Classification/Tagging: Categorizing an entire image based on content (e.g., "contains a cat," "indoor scene," "high quality" vs. "low quality").

2023 - 2024

Education

Work History