Diego B.

Key Skills

Software

Argilla

Appen

Clickworker

Label Studio

CloudFactory

CrowdFlower

CrowdSource

Datature

Datasaur

Datumbox

Datatroniq

Top Subject Matter

Generative AI content auditing and quality control

Medical/scientific literature and clinical case analysis

Sports regulation rules used for criteria enforcement

Top Data Types

Text

Document

Video

Top Task Types

Diagnosis

Segmentation

Classification

Object Detection

Text Generation

Question Answering

Text Summarization

Computer Programming/Coding

Evaluation/Rating

Freelancer Overview

AI Content Auditing & Quality Control (Independent Content & AI Workflows). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Google AI Studio, N, and A. Education includes Bachelor of Medicine, Bachelor of Surgery, Universidad Católica San Antonio de Murcia (UCAM) (2022) and Bachelor of Science, Technical University / Academic Institution. AI-training focus includes data types such as Text, Medical, and DICOM and labeling workflows including Evaluation, Rating, and Diagnosis.

Labeling Experience

AI Content Auditing & Quality Control (Independent Content & AI Workflows)

Text

Provides AI content auditing and quality control for text/video assets produced by automated multi-layer prompt frameworks. Audits advanced model outputs to ensure adherence to complex formatting rules, tone constraints, and visual consistency benchmarks while filtering edge cases for reliable data ingestion. Applies structured evaluation to improve factual accuracy, safety, and logical consistency in generative AI pipelines. • Reviews text and video outputs for factuality and safety • Checks formatting, tone, and visual consistency requirements • Labels and filters edge cases for dataset quality • Ensures outputs are suitable for ingestion into multi-tenant database systems

2025 - Present

Rules Enforcement & Criteria Application (Official Sports Regulation)

Document

Applies strict official sports regulation rules as a basis for consistent evaluation criteria used in AI data labeling taxonomies. Interprets and enforces complex rulebooks in real time to maintain objective decisions under pressure. Uses the same disciplined, criteria-driven mindset to support reliable labeling and rating of data against predefined standards. • Applies hundreds of pages of FIBA technical regulations to live scenarios • Makes precise, objective decisions under intense pressure • Enforces complex criteria sets without personal bias • Supports consistent taxonomy/rubric adherence for labeling

2024 - Present

Medical & Scientific Data Annotation (Academic & Clinical Training Integration)

Diagnosis

Performs medical and scientific data annotation for academic and clinical training contexts. Analyzes and categorizes complex scientific literature, microbiology reports, and human physiology data while verifying factual accuracy and correct logical structuring. Applies careful inspection to detect subtle discrepancies and terminology issues that affect downstream model training and evaluation. • Annotates and categorizes scientific literature and microbiology reports • Reviews human physiology-related data for logical and factual consistency • Validates clinical cases for correct medical terminology • Detects subtle discrepancies in dense, information-heavy documents

2022 - Present

Education

Work History