Emmanuel M.

Key Skills

Software

Appen

Top Subject Matter

AI response quality evaluation (RLHF)

Technical and general content writing for AI/data tasks

Dataset processing/automation for AI training

Top Data Types

Text

Image

Computer Code Programming

Top Task Types

Text Generation

Freelancer Overview

AI Response Rating (RLHF) — AI Trainer & Data Annotator (skills/experience). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include N, A, and Python. Education includes Bachelor of Science, N/A. AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Evaluation, Rating, and Text Generation.

Labeling Experience

Python Developer (Personal Projects) — Ongoing

Built Python scripts to support data processing and automation workflows relevant to annotation pipelines. Handled file operations and data manipulation to prepare or transform datasets for model training and evaluation. Applied programming fundamentals to solve practical data handling problems. • Developed Python data processing scripts • Automated dataset-related tasks • Performed file handling and data manipulation • Supported ongoing learning of AI tools

Present

Freelance Researcher & Content Writer — Ongoing

TextText Generation

Created and refined written research content as part of AI-training-adjacent data work. Produced well-structured text tailored to different audiences and formats for high-quality downstream usage. Maintained a detail-oriented approach to ensure outputs were consistent and reliable. • Conducted in-depth research • Wrote structured content • Adapted content for varied audiences • Performed data entry with verification focus

Present

AI Response Rating (RLHF) — AI Trainer & Data Annotator (skills/experience)

Text

Provided AI response evaluation and rating using RLHF-style feedback to support model quality improvement. Reviewed outputs for quality and relevance to provide accurate scoring signals. Ensured consistency and attention to detail across evaluation tasks. • Evaluated AI responses • Applied RLHF/Evaluation rating criteria • Focused on accuracy and quality • Maintained consistent labeling standards

Present

Education

Work History