Joseph Gomez

Key Skills

Software

Labelbox

Data Annotation Tech

Label Studio

Scale AI

Other

Top Subject Matter

Machine Learning

Computer Vision

Audio Analysis

Top Data Types

Image

Video

Audio

Text

Document

Top Label Types

Bounding Box

Polygon

Point Key Point

Segmentation

Classification

Object Detection

Tracking

Transcription

Freelancer Overview

I have 4+ years of hands-on AI training data and annotation experience across image, video, and audio, backed by advanced ML training and evaluation work. I have labeled bounding boxes, polygons, keypoints, segmentation masks, and classification tags; prepared datasets for object detection and tracking with YOLO; and performed audio tagging and transcription alignment for ASR. My toolkit includes Labelbox, CVAT, Supervisely, VIA, and data versioning, with Python scripting for dataset handling, cleaning, and augmentation. I run rigorous QA with guideline design, inter-annotator agreement checks, spot audits, and error taxonomies to drive consistency and model lift. What sets me apart is end-to-end perspective from data to deployment. At OpenAI (2025–present) I design RLHF procedures, safety evals, and red-teaming that translate labeling quality into measurable model behavior. At Cornell I created datasets and benchmarks for transformer-based NLP research; I also built production pipelines at Google Research and optimized CV models at Microsoft Research. Notable projects include an open-source LLM evaluation toolkit, a medical-imaging system that reached 94% diagnostic accuracy after targeted dataset curation, and a multimodal assistant using CLIP + GPT-4 supported by carefully paired vision–language examples. I communicate clearly with engineers and annotators, manage documentation and versioning, and leverage multilingual skills (English, Spanish, Swahili, French, Korean) for high-quality, culturally aware annotation and review

Labeling Experience

Training Specialist – AI Data Annotation

LabelboxImageBounding BoxPolygon

As a Training Specialist in AI data annotation, I performed data labeling tasks across various media including images, videos, and audio. Tasks included annotating bounding boxes, polygons, key points, segmentation masks, and classification tags to prepare high-quality training datasets for model development. My role also required quality assurance reviews and collaboration with engineers to enhance dataset standards and tracking systems. • Managed versioning and documentation for all labeled datasets. • Organized workflow using tools like Labelbox and YOLO frameworks. • Ensured consistent and accurate labeling practices throughout multiple projects. • Supported model refinement by iteratively updating labeling guidelines based on QA feedback.

As a Training Specialist in AI data annotation, I performed data labeling tasks across various media including images, videos, and audio. Tasks included annotating bounding boxes, polygons, key points, segmentation masks, and classification tags to prepare high-quality training datasets for model development. My role also required quality assurance reviews and collaboration with engineers to enhance dataset standards and tracking systems. • Managed versioning and documentation for all labeled datasets. • Organized workflow using tools like Labelbox and YOLO frameworks. • Ensured consistent and accurate labeling practices throughout multiple projects. • Supported model refinement by iteratively updating labeling guidelines based on QA feedback.

2023 - 2025

Junior Data Annotation Specialist

LabelboxImageBounding BoxSegmentation

As a Junior Data Annotation Specialist, I annotated large-scale image and video datasets for computer vision applications and performed audio tagging and transcription alignment. I assisted in training YOLO-based object detection systems and maintained labeling standards using Labelbox. My duties also included monitoring object tracking accuracy in video sequences and supporting labeling quality. • Worked with images, videos, and audio files to support ML model training. • Utilized Labelbox and other annotation tools for structured data labeling. • Focused on maintaining rigorous QA and consistency within datasets. • Collaborated closely with team members to refine annotation approaches.

As a Junior Data Annotation Specialist, I annotated large-scale image and video datasets for computer vision applications and performed audio tagging and transcription alignment. I assisted in training YOLO-based object detection systems and maintained labeling standards using Labelbox. My duties also included monitoring object tracking accuracy in video sequences and supporting labeling quality. • Worked with images, videos, and audio files to support ML model training. • Utilized Labelbox and other annotation tools for structured data labeling. • Focused on maintaining rigorous QA and consistency within datasets. • Collaborated closely with team members to refine annotation approaches.

2021 - 2021

Education

Work History