Uche Ossai

Key Skills

Software

Mindrift

OneForma

Telus

Toloka

CVAT

Top Subject Matter

Medical & Scientific Image Annotation

Natural Language Processing (NLP)

Computer Vision

Top Data Types

Text

Image

Audio

Top Task Types

Entity (NER) Classification

Object Detection

Prompt + Response Writing (SFT)

Transcription

Fine-tuning

Evaluation/Rating

Text Summarization

Question Answering

Text Generation

Bounding Box

RLHF

Freelancer Overview

Computer Vision Annotator | CVAT (app.cvat.ai) — Independent Practice. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include CVAT, Mindrift, and OneForma. Education includes Bachelor of Science, Federal University of Technology, Owerri (2020). AI-training focus includes data types such as Image and Text and labeling workflows including Bounding Box, RLHF, and Entity (NER) Classification.

Labeling Experience

Computer Vision Annotator | CVAT (app.cvat.ai) — Independent Practice

CVATImageBounding Box

In this role, I performed computer vision image annotation using the CVAT platform with an emphasis on full-spectrum visual labeling. I applied techniques including bounding boxes, polygon segmentation, semantic segmentation, and keypoint detection to medical and scientific images. My contributions supported AI model development in medical, scientific, and research domains. • Executed precise and structured annotation on complex anatomical images. • Maintained label consistency and accuracy across large, multi-class datasets. • Gained proficiency in CVAT tools, including label management and workflow optimization. • Supported dataset curation for training computer vision models for healthcare and research applications.

In this role, I performed computer vision image annotation using the CVAT platform with an emphasis on full-spectrum visual labeling. I applied techniques including bounding boxes, polygon segmentation, semantic segmentation, and keypoint detection to medical and scientific images. My contributions supported AI model development in medical, scientific, and research domains. • Executed precise and structured annotation on complex anatomical images. • Maintained label consistency and accuracy across large, multi-class datasets. • Gained proficiency in CVAT tools, including label management and workflow optimization. • Supported dataset curation for training computer vision models for healthcare and research applications.

2025 - Present

AI Trainer & Data Evaluator | Luel.ai | Mindrift (Remote)

MindriftTextRLHF

As an AI Trainer & Data Evaluator at Luel.ai/Mindrift, I evaluated AI-generated responses for quality, factual accuracy, and coherence to improve RLHF model training. I classified outputs across reasoning, coding, and scientific content tasks using structured guidelines. I consistently delivered high-quality and accurate labels under remote, deadline-driven conditions. • Conducted detailed RLHF and evaluation tasks on NLP, coding, and STEM datasets • Applied complex annotation guidelines to support diverse task evaluations • Utilized physics and STEM background for precise subject-matter annotation • Worked within asynchronous remote team environment for large-scale model improvement

As an AI Trainer & Data Evaluator at Luel.ai/Mindrift, I evaluated AI-generated responses for quality, factual accuracy, and coherence to improve RLHF model training. I classified outputs across reasoning, coding, and scientific content tasks using structured guidelines. I consistently delivered high-quality and accurate labels under remote, deadline-driven conditions. • Conducted detailed RLHF and evaluation tasks on NLP, coding, and STEM datasets • Applied complex annotation guidelines to support diverse task evaluations • Utilized physics and STEM background for precise subject-matter annotation • Worked within asynchronous remote team environment for large-scale model improvement

2024 - Present

Freelance Linguistic Annotator | OneForma (Remote)

OneformaTextEntity Ner Classification

I annotated expansive text datasets for NLP training pipelines aimed at improving conversational AI systems. Assigned sentiment labels, performed named entity recognition, and handled translation alignment across multilingual and domain-diverse text corpora. My contributions went directly into speech recognition and NLP model enhancement projects. • Applied project-specific style guides to maintain dataset quality. • Managed translation and linguistic labels on varied text samples. • Delivered high accuracy and throughput across thousands of data points. • Supported multilingual annotation workflows.

I annotated expansive text datasets for NLP training pipelines aimed at improving conversational AI systems. Assigned sentiment labels, performed named entity recognition, and handled translation alignment across multilingual and domain-diverse text corpora. My contributions went directly into speech recognition and NLP model enhancement projects. • Applied project-specific style guides to maintain dataset quality. • Managed translation and linguistic labels on varied text samples. • Delivered high accuracy and throughput across thousands of data points. • Supported multilingual annotation workflows.

2024 - 2024

AI Data Rater & Annotator | TELUS International AI (Remote)

TelusImageObject Detection

Labeled image and video datasets for computer vision tasks with TELUS International AI, focusing on object detection and scene classification. Evaluated search engine outputs for intent relevance and provided structured feedback for model improvement. Maintained high accuracy over large-scale, long-term annotation projects supporting various machine learning pipelines. • Performed sustained object detection and classification annotation • Rated search relevance and evaluated algorithm outputs • Ensured annotation quality in remote, asynchronous environments • Contributed feedback to iterative AI model cycles

Labeled image and video datasets for computer vision tasks with TELUS International AI, focusing on object detection and scene classification. Evaluated search engine outputs for intent relevance and provided structured feedback for model improvement. Maintained high accuracy over large-scale, long-term annotation projects supporting various machine learning pipelines. • Performed sustained object detection and classification annotation • Rated search relevance and evaluated algorithm outputs • Ensured annotation quality in remote, asynchronous environments • Contributed feedback to iterative AI model cycles

2020 - 2023

Education

Work History