Emmanuel

Key Skills

Software

Other

Humanatic

HiveMind

Scale AI

Top Subject Matter

AI video generation output evaluation (quality/accuracy/safety)

LLM evaluation and RLHF concepts for data annotation

Top Data Types

Video

Text

Image

Top Task Types

RLHF

Polygon

Text Summarization

Fine-tuning

Freelancer Overview

AI & self-directed learning — AI video generation evaluation (RLHF/LLM evaluation focus). Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, University of Cross River State (2025). AI-training focus includes data types such as Video and Text and labeling workflows including Evaluation, Rating, and RLHF. Wokred with Lagrange as a text annotator, image labeling, AI response evaluation,

Labeling Experience

AI training self-study — LLM output evaluation & RLHF annotation readiness

OtherTextRLHF

Performed self-directed study of LLM outputs and how to evaluate them for correctness, relevance, and safety. Explored data annotation platforms and best practices related to RLHF (Reinforcement Learning from Human Feedback). Built an annotation-ready understanding of consistency and precision for human feedback loops. • Practiced evaluating AI-generated text for quality and accuracy • Studied RLHF and how human feedback can refine model outputs • Investigated data annotation platform workflows and best practices • Prepared for long-term involvement in annotation and evaluation tasks

2024 - Present

AI & self-directed learning — AI video generation evaluation (RLHF/LLM evaluation focus)

OtherVideo

Worked with AI video generation tools and studied how to evaluate outputs for quality, accuracy, and safety. Applied a quality-focused mindset from content creation to support annotation and evaluation workflows. Assisted in understanding LLM output reliability and how feedback improves model behavior. • Used AI video tools including Kling AI, Runway ML, Seedance, and Viggle AI for hands-on generation • Focused on assessing tone, relevance, and reliability of AI-generated media • Explored RLHF concepts to understand human-feedback-driven improvement • Intended to apply evaluation practices in remote AI training and annotation projects

2024 - Present

Education

Work History