Philip J.

Key Skills

Software

No software listed

Top Subject Matter

Multilingual Natural Language Processing

Fake News Detection/NLP

Top Data Types

Text

Computer Code Programming

Document

Top Task Types

Classification

Computer Programming/Coding

Fine-tuning

Question Answering

Text Generation

Freelancer Overview

AI Developer & Data Analyst Intern – Language Translation Data Collection & Annotation. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include OpenAI API, Internal, and Proprietary Tooling. Education includes Master of Science, Saint Jean University Institute (2025) and Bachelor of Engineering, African Institute of Computer Science (AICS) (2023). AI-training focus includes data types such as Text and labeling workflows including Translation, Localization, and Classification.

Labeling Experience

AI Developer & Data Analyst Intern – Language Translation Data Collection & Annotation

Text

This internship involved building a French-English to Bamoun translation platform by integrating the OpenAI API for language processing. The role required designing and managing data collection workflows and curating multilingual datasets for training and evaluating translation models. Tasks included defining annotation guidelines, cleaning collected text, and evaluating translations generated by AI systems. • Collected and labeled multilingual text data for supervised training and model evaluation. • Collaborated in curating and verifying translations to improve accuracy. • Utilized Django and OpenAI API for automating data handling workflows. • Managed a structured dataset for ongoing language model fine-tuning.

2023 - 2023

ML/NLP Data Annotator – Fake News Detection Project

TextClassification

Developed a deep learning pipeline for fake news detection using LSTM and RNN architectures with multi-class classification. The process included curating and labeling news datasets as genuine or fake, preprocessing stories, and extracting relevant features. Conducted annotation, validation, and iterative quality checks to maximize model accuracy. • Curated and annotated news article datasets for fake/genuine label assignment. • Processed and tokenized text data for ML pipeline readiness. • Evaluated annotation agreement and refined guidelines as needed. • Used deep learning frameworks and Streamlit for evaluation interface development.

Not specified

Education

Work History