Chimaobi A.

Key Skills

Software

No software listed

Top Subject Matter

Multimodal LLM and vision-model training data (RLHF, safety, annotation guidelines)

Audio annotation and training/evaluation project assessments

Legal Services & Contract Review

Top Data Types

Image

Audio

Text

Document

Top Task Types

Data Collection

Freelancer Overview

AI Advanced Data Trainer (Multimodal Annotation & RLHF Evaluation) | Invisible Technologies. Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Science, Bowen University (2024). AI-training focus includes data types such as Image and Audio and labeling workflows including Evaluation, Rating, and Data Collection.

Labeling Experience

AI Advanced Data Trainer (Audio Annotation & ATP Evaluation Support) | Invisible Technologies

AudioData Collection

Supports audio-related annotation and media assessment projects as part of AI training and evaluation workflows. Applies structured evaluation processes using established frameworks and internal tools to verify dataset suitability for downstream training. Ensures annotated outputs meet accuracy and documentation standards for multilingual, cross-functional collaboration. • Perform audio annotation tasks within AI evaluation projects • Complete ATP Evaluations (Redwood framework) for dataset assessment • Support media literacy assessment labeling activities • Maintain documentation and QA records using internal tooling

2025 - Present

AI Advanced Data Trainer (Multimodal Annotation & RLHF Evaluation) | Invisible Technologies

Image

Works on multimodal annotation and evaluation tasks for LLM training workflows using human labeling validation and model output grading. Performs RLHF-related assessment including preference-ranking evaluation, hallucination detection, and policy-violation flagging to improve safety and quality. Uses internal AI evaluation and data-labeling platforms to ensure consistent dataset curation across distributed teams. • Curate and evaluate multimodal datasets for text, image, reasoning, and instruction-following tasks • Conduct QA validation on human-labeled datasets and maintain benchmark accuracy • Grade and rank model outputs for RLHF/preference workflows while documenting edge cases • Flag hallucinations, harmful outputs, and policy violations as part of bias and safety evaluation

2025 - Present

Education

Work History