Goodness O.

Key Skills

Software

Don't disclose

Top Subject Matter

Large language model (LLM) evaluation and prompt-based testing

AI training methodology support

RLHF-style evaluation

Top Data Types

Text

Document

Top Task Types

RLHF

Freelancer Overview

AI Technical Writer & Model Evaluator (Freelance), Independent Engineering Research (2024 - 2025). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose. Education includes Bachelor of Science, University Level Institution. AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and RLHF.

Labeling Experience

AI training and evaluation activities within Software Engineer & Technical Researcher role, NovaCode Collaborative Ecosystem (2024 - Present)

Don't discloseTextRLHF

Performed AI training support through high-quality dataset annotation and iterative evaluation of model behavior via prompt scenarios aligned to safety and factuality goals. Developed and used structured evaluation frameworks to help validate that model outputs remain optimal, safe, and factual. • Applied RLHF-style methodology emphasis to guide training/evaluation quality. • Used prompt engineering and multi-turn scenarios to probe model constraints. • Conducted systematic error-log and logic evaluation to isolate anomalies. • Focused on quality assurance and compliance-oriented assessment criteria.

2024 - Present

AI Technical Writer & Model Evaluator (Freelance), Independent Engineering Research (2024 - 2025)

Don't discloseText

Reviewed and graded large language model responses for factual accuracy, logical compliance, structural coherence, and safety standards using evaluation-oriented criteria. Authored granular, step-by-step programming guides and technical deep-dives to serve as reference ground-truth data for evaluation engines. • Evaluated LLM outputs for safety and rule-following constraints. • Assessed reasoning quality, coherence, and structural correctness. • Produced ground-truth documentation assets to benchmark evaluation. • Designed edge-case prompt scenarios for robust testing.

2024 - 2025

Education

Work History