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Inime Umanah

AI Trainer & Evaluator Architect – MUDIAN Ltd

United Kingdom flagLondon, United Kingdom
$45.00/hrIntermediateAws Sagemaker

Key Skills

Software

AWS SageMakerAWS SageMaker

Top Subject Matter

Enterprise AI Systems
Llms Domain Expertise
Retrieval-Augmented Generation

Top Data Types

TextText
ImageImage
DocumentDocument

Top Task Types

RLHF
Text Summarization
Classification

Freelancer Overview

AI Trainer & Evaluator Architect – MUDIAN Ltd. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and AWS SageMaker. Education includes Master of Business Administration, N/A and Bachelor of Engineering, N/A. AI-training focus includes data types such as Text, Image, and Document and labeling workflows including Evaluation, Rating, and RLHF.

IntermediateEnglish

Labeling Experience

AI Trainer & Evaluator Architect – MUDIAN Ltd

Text
In this role, I evaluated LLM and RAG outputs for accuracy, helpfulness, safety, and coherence within enterprise AI systems. I annotated and reviewed AI-generated responses to support ongoing model improvement efforts. Additionally, I produced evaluation rubrics, annotation guidelines, and quality assurance documentation for AI workflows. • Evaluated outputs using structured frameworks and documented assessment. • Annotated complex responses to enhance model feedback cycles. • Led the creation of internal guidelines aligned with industry best practices. • Maintained continuous improvement in output review.

In this role, I evaluated LLM and RAG outputs for accuracy, helpfulness, safety, and coherence within enterprise AI systems. I annotated and reviewed AI-generated responses to support ongoing model improvement efforts. Additionally, I produced evaluation rubrics, annotation guidelines, and quality assurance documentation for AI workflows. • Evaluated outputs using structured frameworks and documented assessment. • Annotated complex responses to enhance model feedback cycles. • Led the creation of internal guidelines aligned with industry best practices. • Maintained continuous improvement in output review.

2025 - Present

RAG Document Intelligence Platform

Document
I built and reviewed a semantic search and summarization platform leveraging LangChain and vector databases. I assessed summary quality, factual grounding, and extraction accuracy across large document sets. My annotations and quality checks resulted in optimized retrieval pipelines and reduced processing times. • Evaluated semantic search outputs against benchmarks. • Reviewed factual accuracy in document summarization. • Maintained annotation data integrity. • Streamlined document selection for knowledge extraction.

I built and reviewed a semantic search and summarization platform leveraging LangChain and vector databases. I assessed summary quality, factual grounding, and extraction accuracy across large document sets. My annotations and quality checks resulted in optimized retrieval pipelines and reduced processing times. • Evaluated semantic search outputs against benchmarks. • Reviewed factual accuracy in document summarization. • Maintained annotation data integrity. • Streamlined document selection for knowledge extraction.

2025 - 2025

AI Agents for Workflow Automation

TextClassification
I annotated event-trigger datasets and validated AI agent outputs against pre-defined business rules. My work contributed to automation, decreasing manual processing requirements by a significant margin. Detailed annotation protocols ensured data quality across the project lifecycle. • Classified text triggers in event-driven datasets. • Validated and documented AI agent results. • Developed annotation guidelines for future scalability. • Performed quality checks to maintain dataset integrity.

I annotated event-trigger datasets and validated AI agent outputs against pre-defined business rules. My work contributed to automation, decreasing manual processing requirements by a significant margin. Detailed annotation protocols ensured data quality across the project lifecycle. • Classified text triggers in event-driven datasets. • Validated and documented AI agent results. • Developed annotation guidelines for future scalability. • Performed quality checks to maintain dataset integrity.

2025 - 2025

AI Output Evaluator | MentorPartners

TextRLHF
I assessed LLM-driven outputs for quality, instruction-following, and factual grounding in SaaS AI pipelines. I ranked and compared model responses to generate preference data within human feedback workflows. My feedback contributed directly to RLHF cycles for production AI models. • Compared and ranked diverse AI model outputs. • Identified factual discrepancies and ensured guideline compliance. • Enhanced dataset reliability through consistent scoring. • Supported preference data collection for RLHF training.

I assessed LLM-driven outputs for quality, instruction-following, and factual grounding in SaaS AI pipelines. I ranked and compared model responses to generate preference data within human feedback workflows. My feedback contributed directly to RLHF cycles for production AI models. • Compared and ranked diverse AI model outputs. • Identified factual discrepancies and ensured guideline compliance. • Enhanced dataset reliability through consistent scoring. • Supported preference data collection for RLHF training.

2024 - 2025

AI Tester & Prompt Engineer | SprintLab Digital

Text
I delivered end-to-end solutions for LLM and Generative AI implementations, including prompt design and model evaluation. I created technical briefs and evaluated model outputs for quality and fitness to business requirements. This involved detailed examination and documentation of AI system performance. • Designed prompts and evaluated responses for completeness. • Developed business-ready documentation based on evaluation outcomes. • Assessed model behavior to inform further fine-tuning. • Coordinated with clients to iterate on annotated feedback.

I delivered end-to-end solutions for LLM and Generative AI implementations, including prompt design and model evaluation. I created technical briefs and evaluated model outputs for quality and fitness to business requirements. This involved detailed examination and documentation of AI system performance. • Designed prompts and evaluated responses for completeness. • Developed business-ready documentation based on evaluation outcomes. • Assessed model behavior to inform further fine-tuning. • Coordinated with clients to iterate on annotated feedback.

2024 - 2024

Education

N

N/A

Diploma, Computer Science

Diploma
Not specified
N

N/A

Bachelor of Engineering, Chemical Engineering

Bachelor of Engineering
Not specified

Work History

A

Almond Media

Cloud Engineer & Data Engineer

London
2022 - 2024