Michael Samaniego

Key Skills

Software

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Image

Video

Top Label Types

Bounding Box

Point Key Point

Segmentation

Classification

Tracking

Freelancer Overview

I am an experienced AI Training Specialist with over three years of hands-on expertise in data annotation, dataset preparation, and supporting AI model development across computer vision and speech domains. My background includes leading complex annotation projects involving image, video, and audio data, with a strong focus on object detection, semantic and instance segmentation, multi-object tracking, and audio transcription for ASR models. I am proficient with industry-standard tools such as Labelbox, Supervisely, Roboflow, and Amazon SageMaker Ground Truth, and have contributed to projects that improved model accuracy for autonomous systems and voice AI. My approach emphasizes quality assurance, error analysis, and structured review protocols to ensure high-accuracy datasets and reliable machine learning outcomes. I thrive in collaborative, remote environments and bring strong analytical skills, attention to detail, and a commitment to data integrity and compliance.

Labeling Experience

Computer Vision & Audio Data Annotation Project

LabelboxVideoBounding BoxPoint Key Point

Annotated video datasets for computer vision AI models, performing frame-by-frame object detection, multi-object tracking, and activity labeling. Used tools such as Labelbox, CVAT, and Supervisely to create bounding boxes, polygons, and keypoint annotations. Ensured high-quality and consistent labeling by performing regular quality checks and dataset validation. Collaborated with ML engineers to optimize YOLO-based models and improve overall model accuracy. Managed large-scale video datasets and maintained workflow efficiency to meet project deadlines.

Annotated video datasets for computer vision AI models, performing frame-by-frame object detection, multi-object tracking, and activity labeling. Used tools such as Labelbox, CVAT, and Supervisely to create bounding boxes, polygons, and keypoint annotations. Ensured high-quality and consistent labeling by performing regular quality checks and dataset validation. Collaborated with ML engineers to optimize YOLO-based models and improve overall model accuracy. Managed large-scale video datasets and maintained workflow efficiency to meet project deadlines.

2024

Computer Vision & Audio Data Annotation Project

LabelboxImageBounding BoxPoint Key Point

Led Large-scale annotation projects involving image,video and audio datasets for AI model training.Perfomed bounding box,polygon,semantic segmentation,keypoint annotation,and multi-object tracking using tools such as Labelbox and CVAT.Annotated and timestamped audio data for speech recognition systems.Conducted dataset validation,quality assurance reviews,and error correction to mantain 98% annotation accuracy.Collaborated with machine learning engineers to optimize YOLO-based object detection models and improve overall dataset perfomance.

Led Large-scale annotation projects involving image,video and audio datasets for AI model training.Perfomed bounding box,polygon,semantic segmentation,keypoint annotation,and multi-object tracking using tools such as Labelbox and CVAT.Annotated and timestamped audio data for speech recognition systems.Conducted dataset validation,quality assurance reviews,and error correction to mantain 98% annotation accuracy.Collaborated with machine learning engineers to optimize YOLO-based object detection models and improve overall dataset perfomance.

2021 - 2024

Education

Work History