For employers

Hire this AI Trainer

Sign in or create an account to invite AI Trainers to your job.

LoginCreate account
Invite to Job
E

Emmanuel Oluwatomiwa

AI Prompt Engineer & Evaluator (Freelance)

NIGERIA flag
N/A, Nigeria
$35.00/hrIntermediateAppenData Annotation TechMercor

Key Skills

Software

AppenAppen
Data Annotation TechData Annotation Tech
MercorMercor
OneFormaOneForma

Top Subject Matter

AI/LLM Output Evaluation
Annotation Domain Expertise
RLHF AND Labelling

Top Data Types

TextText
AudioAudio
DocumentDocument

Top Task Types

Entity Ner Classification
Object Detection
Text Generation
Question Answering
RLHF
Text Summarization
Fine Tuning
Evaluation Rating
Prompt Response Writing SFT
Segmentation

Freelancer Overview

AI Prompt Engineer & Evaluator (Freelance). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Science, Federal University of Nigeria (2024). AI-training focus includes data types such as Text and Audio and labeling workflows including Evaluation, Rating, and Entity (NER) Classification.

IntermediateEnglish

Labeling Experience

Voice AI Agent Evaluator & Labeller

Audio
I assessed the speech-to-text transcription quality and conversational AI flow for Voice AI agents in customer interaction scenarios. My annotation included labeling transcription accuracy, routing failures, and specifying escalation triggers for human intervention. The labeled data directly improved agent reliability and user satisfaction. • Evaluated audio outputs for transcription fidelity and intent • Labeled and routed out-of-scope agent responses • Defined criteria for conversational handoff to human agents • Enhanced overall speech AI flow and resolution processes

I assessed the speech-to-text transcription quality and conversational AI flow for Voice AI agents in customer interaction scenarios. My annotation included labeling transcription accuracy, routing failures, and specifying escalation triggers for human intervention. The labeled data directly improved agent reliability and user satisfaction. • Evaluated audio outputs for transcription fidelity and intent • Labeled and routed out-of-scope agent responses • Defined criteria for conversational handoff to human agents • Enhanced overall speech AI flow and resolution processes

2023 - Present

AI Message Annotator (Twitter/X Bot)

Text
I evaluated and annotated edge-case responses of AI-driven social media bots, focusing on context coherence and topic alignment. My structured labeling enabled developers to refine prompt strategies and mitigate off-topic model behaviors. Regular feedback cycles addressed subtle errors in message generation. • Tagged Twitter/X bot responses for tone, context, and drift • Flagged out-of-scope or misunderstood content in social interactions • Delivered annotation data for prompt refinement and QA • Assisted in maintaining brand-appropriate online presence

I evaluated and annotated edge-case responses of AI-driven social media bots, focusing on context coherence and topic alignment. My structured labeling enabled developers to refine prompt strategies and mitigate off-topic model behaviors. Regular feedback cycles addressed subtle errors in message generation. • Tagged Twitter/X bot responses for tone, context, and drift • Flagged out-of-scope or misunderstood content in social interactions • Delivered annotation data for prompt refinement and QA • Assisted in maintaining brand-appropriate online presence

2023 - Present

RAG Pipeline Output Annotator

Text
Within a Retrieval-Augmented Generation (RAG) pipeline for retail and support AI agents, I labeled AI-generated outputs for relevance, completeness, and faithfulness to source documents. The annotation process improved knowledge-base response accuracy and platform reliability. My efforts ensured robust 24/7 automated support for end users. • Validated model-generated answers against retrieved chunks • Identified and labeled irrelevant or inaccurate agent responses • Supported RAG pipeline performance monitoring and QA • Enhanced customer interaction outcomes through structured feedback

Within a Retrieval-Augmented Generation (RAG) pipeline for retail and support AI agents, I labeled AI-generated outputs for relevance, completeness, and faithfulness to source documents. The annotation process improved knowledge-base response accuracy and platform reliability. My efforts ensured robust 24/7 automated support for end users. • Validated model-generated answers against retrieved chunks • Identified and labeled irrelevant or inaccurate agent responses • Supported RAG pipeline performance monitoring and QA • Enhanced customer interaction outcomes through structured feedback

2023 - Present

AI Data Annotator (Email Entity Extraction)

TextEntity Ner Classification
I curated structured test suites of real-world email data to benchmark an AI CRM Agent's information extraction abilities. My work involved annotating key entities such as name, intent, and contact info in JSON format, ensuring high-precision and recall. I maintained annotation consistency and zero-error extraction through careful design and review. • Labeled named entities critical for sales and CRM workflows • Translated unstructured email content into structured data for LLM training • Developed precise annotation guidelines and test cases • Audited outputs to guarantee extraction accuracy and completeness

I curated structured test suites of real-world email data to benchmark an AI CRM Agent's information extraction abilities. My work involved annotating key entities such as name, intent, and contact info in JSON format, ensuring high-precision and recall. I maintained annotation consistency and zero-error extraction through careful design and review. • Labeled named entities critical for sales and CRM workflows • Translated unstructured email content into structured data for LLM training • Developed precise annotation guidelines and test cases • Audited outputs to guarantee extraction accuracy and completeness

2023 - Present

AI Prompt Engineer & Evaluator (Freelance)

Text
As an AI Prompt Engineer & Evaluator, I systematically evaluated, annotated, and quality-assured Large Language Model outputs for multiple enterprise clients. My responsibilities included designing annotation guidelines, scoring AI responses, and delivering high-quality labeled datasets for training and alignment. I applied rigorous quality standards to reduce hallucinations, misclassification, and improve model behaviors through structured feedback. • Assessed LLM outputs for quality, factual grounding, safety, and tone adherence • Annotated and curated data for RAG pipelines and real-world application agents • Built structured test sets, few-shot examples, and benchmarks for model fine-tuning • Provided feedback loops to cut lead qualification time and escalate edge cases

As an AI Prompt Engineer & Evaluator, I systematically evaluated, annotated, and quality-assured Large Language Model outputs for multiple enterprise clients. My responsibilities included designing annotation guidelines, scoring AI responses, and delivering high-quality labeled datasets for training and alignment. I applied rigorous quality standards to reduce hallucinations, misclassification, and improve model behaviors through structured feedback. • Assessed LLM outputs for quality, factual grounding, safety, and tone adherence • Annotated and curated data for RAG pipelines and real-world application agents • Built structured test sets, few-shot examples, and benchmarks for model fine-tuning • Provided feedback loops to cut lead qualification time and escalate edge cases

2023 - Present

Education

F

Federal University of Nigeria

Bachelor of Science, Radiography

Bachelor of Science
2024 - 2024

Work History

F

Freelance

Freelance Research and Data Analyst

N/A
2024 - 2024