Robert Cossin

Key Skills

Software

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Image

Video

Top Label Types

Bounding Box

Segmentation

Classification

Object Detection

Tracking

Point Key Point

Freelancer Overview

I am an experienced AI Training Specialist with over three years of hands-on expertise in data labeling and annotation for computer vision and audio-based machine learning systems. My background includes preparing and annotating large-scale image, video, and audio datasets using tools like Labelbox, CVAT, Supervisely, Roboflow, and VGG Image Annotator. I am skilled in creating precise bounding boxes, polygons, keypoints, and segmentation masks, as well as working with YOLO, COCO, and Pascal VOC formats. My experience covers object detection, object tracking (using SORT and DeepSORT), and audio annotation for transcription and speech-to-text models. I consistently maintain annotation accuracy above 98% through rigorous quality checks and collaborate closely with ML engineers to refine labeling guidelines. My technical skills also include basic Python for dataset preprocessing, data formatting, and quality assurance, ensuring reliable and high-quality training data for AI model development.

Labeling Experience

High Precision Multimodal Data Annotation for Computer Vision Models

LabelboxVideoBounding BoxPoint Key Point

Currently contributing to a large-scale video annotation project focused on training high-performance computer vision models. The project involves frame-by-frame labeling of dynamic scenes to improve object detection, tracking, and action recognition systems.

Currently contributing to a large-scale video annotation project focused on training high-performance computer vision models. The project involves frame-by-frame labeling of dynamic scenes to improve object detection, tracking, and action recognition systems.

2023 - 2025

Autonomous Vehicle Object Detection & Multi-Object Tracking Dataset

LabelboxImageBounding BoxSegmentation

Worked on a large-scale computer vision dataset for autonomous vehicle perception systems. The project involved annotating over 150,000 image frames and 2,500+ video sequences captured from urban and highway environments.

Worked on a large-scale computer vision dataset for autonomous vehicle perception systems. The project involved annotating over 150,000 image frames and 2,500+ video sequences captured from urban and highway environments.

2023 - 2023

Education

Work History