Zambrano F.

Key Skills

Software

Labelbox

CVAT

Supervisely

Top Subject Matter

General Machine Learning/AI Model Training

Legal Services & Contract Review

Regulatory Compliance & Risk Analysis

Top Data Types

Image

Video

Audio

Text

Document

Top Task Types

Bounding Box

Point/Key Point

Classification

Tracking

Emotion Recognition

Audio Recording

Object Detection

Freelancer Overview

AI Training Specialist / Data Annotator — Remote Contract Work. Brings 5+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Labelbox, YODO Annotation Platform, and CVAT. Education includes High School Diploma, N/A (2024). AI-training focus includes data types such as Image and labeling workflows including Object Detection.

Labeling Experience

AI Training Data Annotation — Multi-Modal Dataset

LabelboxImageBounding BoxPoint/Key Point

Annotated large-scale image, vedio, and audio datasets for machine learning training and evaluation. Performed object detection using bounding boxes, semantic segmentation, classification tagging, and audio transcription. Ensured strict adherence to annotation guidelines to maintain dataset accuracy and consistency. Conducted quality assurance reviews to identify labeling errors and improve dataset reliability. Contributed to the preparation of structured training data used to enhance AI model performance across computer vision and speech-related tasks.

2022 - Present

AI Training Data Annotation — Multi-Modal Dataset

CVATAudioBounding BoxPoint/Key Point

Annotated large-scale audio datasets for machine learning and AI model training. Performed tasks including transcription, speaker identification, emotion recognition, and sound event labeling. Ensured high-quality annotations by following strict guidelines and performing quality checks for clarity, accuracy, and consistency. Prepared structured audio training data used to improve speech recognition, natural language understanding, and audio-based AI models.

2024 - 2025

AI Training Data Annotation — Multi-Modal Dataset

LabelboxVideoBounding BoxPoint/Key Point

Annotated large-scale video datasets for machine learning and computer vision model training. Performed frame-by-frame labeling using bounding boxes and segmentation to identify objects, human activities, and motion patterns. Conducted action recognition and object tracking across continuous video sequences to ensure temporal consistency. Applied strict annotation guidelines and performed quality assurance reviews to maintain high accuracy and dataset reliability. Contributed structured, high-quality video training data to improve model performance in detection, tracking, and behavior analysis tasks.

2023 - 2024

Education

Work History