Abidakun Ololade

Key Skills

Software

Appen

Data Annotation Tech

OneForma

Mindrift

Telus

Scale AI

Other

Top Subject Matter

Large Language Models

General AI Applications

Natural Language Processing

Top Data Types

Video

Text

Audio

Image

Document

Top Task Types

Transcription

Evaluation/Rating

Data Collection

Prompt + Response Writing (SFT)

Question Answering

Text Generation

Red Teaming

Fine-tuning

Freelancer Overview

Quality Assurance Specialist – LLM & AI Model Evaluation. Brings 11+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Telus, Scale AI, and Appen. Education includes Master of Science, University of California (2018) and Bachelor of Science, University of Lagos (2016). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Data Collection.

Labeling Experience

Content Reviewer & AI Output Quality Analyst

OtherText

As a Freelance Content Reviewer & AI Output Quality Analyst, I audited and reviewed AI-generated text content, translations, and captions for quality assurance. The work spanned multiple domains, with an emphasis on ethical compliance, factual accuracy, and stylistic improvements. My structured feedback supported model developers in improving output fluency and compliance. • Conducted linguistic and contextual reviews of AI-generated content for healthcare, education, and STEM projects. • Audited data annotation projects for ethical and factual quality standards. • Provided feedback on misalignment and identified tone correction needs. • Enhanced QA compliance and streamlined audit turnaround times.

As a Freelance Content Reviewer & AI Output Quality Analyst, I audited and reviewed AI-generated text content, translations, and captions for quality assurance. The work spanned multiple domains, with an emphasis on ethical compliance, factual accuracy, and stylistic improvements. My structured feedback supported model developers in improving output fluency and compliance. • Conducted linguistic and contextual reviews of AI-generated content for healthcare, education, and STEM projects. • Audited data annotation projects for ethical and factual quality standards. • Provided feedback on misalignment and identified tone correction needs. • Enhanced QA compliance and streamlined audit turnaround times.

2022 - Present

Quality Assurance Specialist – LLM & AI Model Evaluation

TelusText

As a Quality Assurance Specialist for LLM & AI model evaluation at TELUS International, I was responsible for evaluating, scoring, and auditing AI-generated text outputs. The work included developing rubrics, performing linguistic assessments, and providing detailed feedback to improve model alignment and user safety. My efforts contributed to increased accuracy, coherence, and bias mitigation within large language models. • Conducted evaluation and structured QA on text-based LLM outputs across various domains. • Developed and refined model assessment rubrics for tone, coherence, and factuality. • Collaborated with engineers to address prompt misalignment and response quality. • Supported iterative improvements by providing granular scoring and error categorization.

As a Quality Assurance Specialist for LLM & AI model evaluation at TELUS International, I was responsible for evaluating, scoring, and auditing AI-generated text outputs. The work included developing rubrics, performing linguistic assessments, and providing detailed feedback to improve model alignment and user safety. My efforts contributed to increased accuracy, coherence, and bias mitigation within large language models. • Conducted evaluation and structured QA on text-based LLM outputs across various domains. • Developed and refined model assessment rubrics for tone, coherence, and factuality. • Collaborated with engineers to address prompt misalignment and response quality. • Supported iterative improvements by providing granular scoring and error categorization.

2020 - Present

STEM Domain AI Trainer & Evaluation Specialist

TextFine Tuning

As a STEM Domain AI Trainer & Evaluation Specialist at DataForce by TransPerfect, I reviewed and curated datasets for model training in scientific and technical subject areas. My work included building evaluation rubrics and direct involvement in factuality validation and alignment. These efforts resulted in measurable improvements in STEM LLM performance. • Carried out response review and labeling for STEM-related AI model outputs. • Developed domain-specific evaluation rubrics and quality benchmarks. • Participated in dataset curation for question answering and fine-tuning. • Contributed to increased factual accuracy and trust in scientific AI systems.

As a STEM Domain AI Trainer & Evaluation Specialist at DataForce by TransPerfect, I reviewed and curated datasets for model training in scientific and technical subject areas. My work included building evaluation rubrics and direct involvement in factuality validation and alignment. These efforts resulted in measurable improvements in STEM LLM performance. • Carried out response review and labeling for STEM-related AI model outputs. • Developed domain-specific evaluation rubrics and quality benchmarks. • Participated in dataset curation for question answering and fine-tuning. • Contributed to increased factual accuracy and trust in scientific AI systems.

2019 - 2022

Linguistic QA & Data Annotation Specialist

Scale AITextData Collection

At Scale AI, I served as a Linguistic QA & Data Annotation Specialist, focusing on the annotation and validation of multilingual datasets for LLM training. My tasks involved both content QA and systematic error categorization for AI models. This role required a mix of annotation precision and structured workflow optimization. • Annotated and validated text data for LLM and chatbot model training. • Executed context and linguistic QA on AI-generated responses in multiple languages. • Collaborated to create and refine team-wide annotation guidelines. • Received recognition for annotation and QA performance improvements.

At Scale AI, I served as a Linguistic QA & Data Annotation Specialist, focusing on the annotation and validation of multilingual datasets for LLM training. My tasks involved both content QA and systematic error categorization for AI models. This role required a mix of annotation precision and structured workflow optimization. • Annotated and validated text data for LLM and chatbot model training. • Executed context and linguistic QA on AI-generated responses in multiple languages. • Collaborated to create and refine team-wide annotation guidelines. • Received recognition for annotation and QA performance improvements.

2018 - 2020

Search Engine Evaluation & Content Reviewer

AppenText

While working as a Search Engine Evaluation & Content Reviewer at Appen/RaterLabs, I evaluated the relevance and quality of search engine outputs. The work involved structured content checks and detailed feedback for algorithmic improvement. Tasks required maintaining high accuracy in content rating and relevance assessment. • Performed search result evaluation and relevance rating on English-language datasets. • Conducted quality checks for AI-generated snippets and media metadata. • Provided structured feedback to inform algorithm adjustments and NLP ranking. • Achieved high-precision ratings and consistent task accuracy.

While working as a Search Engine Evaluation & Content Reviewer at Appen/RaterLabs, I evaluated the relevance and quality of search engine outputs. The work involved structured content checks and detailed feedback for algorithmic improvement. Tasks required maintaining high accuracy in content rating and relevance assessment. • Performed search result evaluation and relevance rating on English-language datasets. • Conducted quality checks for AI-generated snippets and media metadata. • Provided structured feedback to inform algorithm adjustments and NLP ranking. • Achieved high-precision ratings and consistent task accuracy.

2016 - 2018

Education

Work History