Key Skills

Software

AWS SageMaker

Appen

Clickworker

CVAT

Data Annotation Tech

Google Cloud Vertex AI

iMerit

Labelbox

Mercor

Mighty AI

Mindrift

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Image

Video

Top Task Types

Action Recognition

Bounding Box

Classification

Computer Programming Coding

Data Collection

Freelancer Overview

I have hands-on experience in data labeling and AI training workflows, specializing in creating high-quality datasets that power machine learning and natural language processing applications. My background includes working with diverse data types—text, image, audio, and video—where I ensured accuracy, consistency, and compliance with project guidelines. I am skilled in annotation, categorization, and quality assurance, with a strong eye for detail and the ability to balance efficiency with precision. Beyond labeling, I bring a deep understanding of AI model development and deployment, supported by certifications in Google Cloud Professional Machine Learning and ongoing specialization in deep learning, NLP, and MLOps. I have contributed to projects involving text classification, entity recognition, sentiment analysis, and image annotation, combining technical expertise with a problem-solving mindset. My ability to adapt quickly to new tools and processes, along with my passion for building reliable AI systems, enables me to deliver high-value contributions to any AI training or data-centric project.

Labeling Experience

Data Specialist

Scale AIComputer Code ProgrammingRLHFComputer Programming Coding

I contributed to the enhancement of the Aider software testing benchmark, where I focused on improving AI-driven code generation and evaluation. My work involved refining benchmark design, assessing model performance, and ensuring higher accuracy and reliability in testing workflows. This project strengthened my expertise in data quality, model evaluation, and AI system improvement, while also giving me practical experience in how carefully curated benchmarks can directly enhance the performance and trustworthiness of AI tools.

I contributed to the enhancement of the Aider software testing benchmark, where I focused on improving AI-driven code generation and evaluation. My work involved refining benchmark design, assessing model performance, and ensuring higher accuracy and reliability in testing workflows. This project strengthened my expertise in data quality, model evaluation, and AI system improvement, while also giving me practical experience in how carefully curated benchmarks can directly enhance the performance and trustworthiness of AI tools.

2025 - 2025

Education

Work History