Terna Ugoh

Key Skills

Software

Telus

Lionbridge

Toloka

Other

Top Subject Matter

Generative AI/LLMs

Search Engines/ML Data Quality

Search Engines/AI Search Quality

Top Data Types

Text

Image

Video

Top Task Types

Classification

Text Generation

Text Summarization

RLHF

Fine-tuning

Transcription

Evaluation/Rating

Question Answering

Data Collection

Freelancer Overview

an AI Training Specialist or LLM Evaluator. With over eight (8) years of dedicated experience in AI data evaluation, search quality assessment, and machine learning dataset quality assurance — working with industry leaders such as Turing Enterprises Inc., TELUS International A.I., and Lionbridge A.I. (Google) — I bring a deep and proven understanding of what it takes to improve the accuracy, reliability, and helpfulness of AI systems. In my most recent role at Turing Enterprises Inc., I specialised in side-by-side (SxS) evaluations of large language model outputs, assessing responses for factual accuracy, logical coherence, instruction-following, and overall quality. I have consistently demonstrated the ability to produce detailed, structured justifications for evaluation decisions, follow complex annotation guidelines with precision, and communicate insights that directly influence model improvement cycles. Prior to this, I spent over six years at TELUS International and Lionbridge evaluating and rating real-world AI and search engine outputs — developing a sharp instinct for relevance, content quality, and user intent. I am detail-oriented, self-directed, and experienced in remote workflows — qualities I have refined across multiple contract and full-time positions.

Labeling Experience

Turing Enterprises, Inc. - Business Analyst.

TextRLHF

In this role, I conducted side-by-side (SxS) evaluations of generative AI outputs for accuracy and relevance. I performed rigorous fact-checking and provided structured feedback to inform AI model improvements. Detailed evaluation justifications were documented to align with established quality standards. • Assessed LLM-generated text using browser-based and command-line tools. • Evaluated factual correctness and identified hallucinations or inconsistencies. • Communicated findings to stakeholders for model enhancement. • Focused on improving overall AI output quality through structured analysis.

In this role, I conducted side-by-side (SxS) evaluations of generative AI outputs for accuracy and relevance. I performed rigorous fact-checking and provided structured feedback to inform AI model improvements. Detailed evaluation justifications were documented to align with established quality standards. • Assessed LLM-generated text using browser-based and command-line tools. • Evaluated factual correctness and identified hallucinations or inconsistencies. • Communicated findings to stakeholders for model enhancement. • Focused on improving overall AI output quality through structured analysis.

2026 - 2026

Internet Assessor (Nigeria)

TelusText

As an Internet Assessor, I evaluated and rated online data to improve AI-powered search model accuracy. Analysis focused on the relevance and intent alignment of search queries and web content. Annotation consistency was optimized across large-scale machine learning datasets. • Rated and evaluated various types of web data for quality improvement. • Applied data quality principles to maintain high annotation standards. • Directly enhanced data integrity for machine learning applications. • Supported the optimization of global search engine models.

As an Internet Assessor, I evaluated and rated online data to improve AI-powered search model accuracy. Analysis focused on the relevance and intent alignment of search queries and web content. Annotation consistency was optimized across large-scale machine learning datasets. • Rated and evaluated various types of web data for quality improvement. • Applied data quality principles to maintain high annotation standards. • Directly enhanced data integrity for machine learning applications. • Supported the optimization of global search engine models.

2021 - 2024

Search Engine Quality Rater (Google)

LionbridgeText

I assessed and rated Google search results to support the refinement of AI search algorithms. Maintaining annotation dataset accuracy was crucial to enhancing model reliability and performance. Structured feedback was provided to help machine learning teams improve search quality metrics. • Rated search results based on relevance and intent. • Ensured consistency and quality in large-scale annotation projects. • Contributed to improved accuracy of AI-powered search systems. • Supported continuous model evaluation and enhancement.

I assessed and rated Google search results to support the refinement of AI search algorithms. Maintaining annotation dataset accuracy was crucial to enhancing model reliability and performance. Structured feedback was provided to help machine learning teams improve search quality metrics. • Rated search results based on relevance and intent. • Ensured consistency and quality in large-scale annotation projects. • Contributed to improved accuracy of AI-powered search systems. • Supported continuous model evaluation and enhancement.

2017 - 2021

Education

Work History