Victor Inegbeniki

Key Skills

Software

Appen

CVAT

Top Subject Matter

No subject matter listed

Top Data Types

Image

Top Label Types

Bounding Box

Text Generation

RLHF

Fine Tuning

Evaluation Rating

Freelancer Overview

I am an experienced AI data trainer and human-in-the-loop specialist with a strong background in data labeling, annotation, and model evaluation for NLP, computer vision, and RLHF workflows. Over the past two years, I have worked remotely on high-impact projects with platforms such as Scale AI, Remotasks, Appen, and Outlier AI, consistently delivering high-quality annotations and maintaining accuracy scores above 95%. My expertise includes prompt engineering, response ranking, and providing structured feedback to improve large language models. I am skilled in using a variety of labeling tools like Labelbox, CVAT, and Surge AI, and have contributed to domains such as medical, biology, creative writing, and general interest. I am passionate about ensuring data quality and collaborating with teams to drive continuous model improvement in fast-paced environments.

Labeling Experience

AI audio data trainer

CVATAudioClassificationQuestion Answering

prompting audio to text and audio comparisons, audio annotations and audio prompt fine tuning Bounding box with labels Image removal and replacement via prompts and voice prompts labelling various voice recording for disparities. Transcribed, labeled, and quality-checked audio datasets including speech recordings, background noise samples, and multilingual utterances to train automatic speech recognition (ASR) models. Evaluated AI-generated audio transcriptions for accuracy, fluency, and speaker diarization, maintaining a quality score above 80%. Annotated emotional tone, intent, and sentiment in spoken audio clips to support conversational AI and voice assistant model training

prompting audio to text and audio comparisons, audio annotations and audio prompt fine tuning Bounding box with labels Image removal and replacement via prompts and voice prompts labelling various voice recording for disparities. Transcribed, labeled, and quality-checked audio datasets including speech recordings, background noise samples, and multilingual utterances to train automatic speech recognition (ASR) models. Evaluated AI-generated audio transcriptions for accuracy, fluency, and speaker diarization, maintaining a quality score above 80%. Annotated emotional tone, intent, and sentiment in spoken audio clips to support conversational AI and voice assistant model training

2024 - 2025

label expert

AppenImageBounding BoxText Generation

• Judge (in RLHF tasks, by ranking responses). • Grader (in Evaluation tasks, by scoring against a rubric). • Safety Inspector (in Red Teaming tasks, by finding vulnerabilities).

• Judge (in RLHF tasks, by ranking responses). • Grader (in Evaluation tasks, by scoring against a rubric). • Safety Inspector (in Red Teaming tasks, by finding vulnerabilities).

2024 - 2025

Education

Work History