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I’m Francis Wanyoike Muiruri, an AI Quality Analyst and LLM Evaluation Specialist based in Nairobi (remote). I evaluate AI-generated responses and reasoning-heavy outputs against clear quality standards—focusing on accuracy, relevance, clarity, coherence, completeness, and strong instruction following. My work often involves comparing multiple model outputs side-by-side to identify subtle differences, unsupported claims, logical gaps, and other issues that affect user usefulness and reliability. I also support prompt and conversation testing by designing evaluation scenarios that measure comprehension, grounding/factuality, and edge-case behavior in multi-turn interactions. Alongside evaluation, I’ve contributed to structured dataset work through annotation, guideline-based scoring, and taxonomy adherence, and I’ve produced clear, evidence-based feedback to help teams improve both responses and evaluation frameworks. I’m fluent professionally in English and comfortable working independently on task-based, remote workflows with high consistency and attention to detail.…I’m Francis Wanyoike Muiruri, an AI Quality Analyst and LLM Evaluation Specialist based in Nairobi (remote). I evaluate AI-generated responses and reasoning-heavy outputs against clear quality standards—focusing on accuracy, relevance, clarity, coherence, completeness, and strong instruction following. My work often involves comparing multiple model outputs side-by-side to identify subtle differences, unsupported claims, logical gaps, and other issues that affect user usefulness and reliability. I also support prompt and conversation testing by designing evaluation scenarios that measure comprehension, grounding/factuality, and edge-case behavior in multi-turn interactions. Alongside evaluation, I’ve contributed to structured dataset work through annotation, guideline-based scoring, and taxonomy adherence, and I’ve produced clear, evidence-based feedback to help teams improve both responses and evaluation frameworks. I’m fluent professionally in English and comfortable working independently on task-based, remote workflows with high consistency and attention to detail.

Francis Wanyoike Muiruri

QA Engineer, AI Evaluator, AI Engineer, +1

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I’m Francis Wanyoike Muiruri, an AI Quality Analyst and LLM Evaluation Specialist based in Nairobi (remote). I evaluate AI-generated responses and reasoning-heavy outputs against clear quality standards—focusing on accuracy, relevance, clarity, coherence, completeness, and strong instruction following. My work often involves comparing multiple model outputs side-by-side to identify subtle differences, unsupported claims, logical gaps, and other issues that affect user usefulness and reliability. I also support prompt and conversation testing by designing evaluation scenarios that measure comprehension, grounding/factuality, and edge-case behavior in multi-turn interactions. Alongside evaluation, I’ve contributed to structured dataset work through annotation, guideline-based scoring, and taxonomy adherence, and I’ve produced clear, evidence-based feedback to help teams improve both responses and evaluation frameworks. I’m fluent professionally in English and comfortable working independently on task-based, remote workflows with high consistency and attention to detail.…I’m Francis Wanyoike Muiruri, an AI Quality Analyst and LLM Evaluation Specialist based in Nairobi (remote). I evaluate AI-generated responses and reasoning-heavy outputs against clear quality standards—focusing on accuracy, relevance, clarity, coherence, completeness, and strong instruction following. My work often involves comparing multiple model outputs side-by-side to identify subtle differences, unsupported claims, logical gaps, and other issues that affect user usefulness and reliability. I also support prompt and conversation testing by designing evaluation scenarios that measure comprehension, grounding/factuality, and edge-case behavior in multi-turn interactions. Alongside evaluation, I’ve contributed to structured dataset work through annotation, guideline-based scoring, and taxonomy adherence, and I’ve produced clear, evidence-based feedback to help teams improve both responses and evaluation frameworks. I’m fluent professionally in English and comfortable working independently on task-based, remote workflows with high consistency and attention to detail.

Available to hire

I’m Francis Wanyoike Muiruri, an AI Quality Analyst and LLM Evaluation Specialist based in Nairobi (remote). I evaluate AI-generated responses and reasoning-heavy outputs against clear quality standards—focusing on accuracy, relevance, clarity, coherence, completeness, and strong instruction following. My work often involves comparing multiple model outputs side-by-side to identify subtle differences, unsupported claims, logical gaps, and other issues that affect user usefulness and reliability.

I also support prompt and conversation testing by designing evaluation scenarios that measure comprehension, grounding/factuality, and edge-case behavior in multi-turn interactions. Alongside evaluation, I’ve contributed to structured dataset work through annotation, guideline-based scoring, and taxonomy adherence, and I’ve produced clear, evidence-based feedback to help teams improve both responses and evaluation frameworks. I’m fluent professionally in English and comfortable working independently on task-based, remote workflows with high consistency and attention to detail.

Skills

Experience Level

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Swahili

Fluent

Polish

Advanced

Work Experience

AI Evaluation & Instructional Content Specialist at Vetto AI

January 1, 2023 - Present

Supported advanced AI training and evaluation workflows by assessing AI-generated responses and reasoning-heavy outputs against structured criteria (accuracy, relevance, clarity, coherence, reasoning quality, completeness, and instruction adherence). Performed comparative side-by-side analysis across multiple model outputs, ranking responses and explaining decisions with concise, evidence-based rationales. Designed and evaluated prompts and evaluation scenarios to test reasoning, comprehension, instruction following, and conversational quality, including multi-turn settings and edge cases. Identified factual inconsistencies, unsupported claims, contextual errors, ambiguities, and logical gaps, and contributed to refinement of evaluation guidelines used in AI training workflows.

Digital Content & Educational Quality Analyst at Vetto

January 1, 2021 - January 1, 2023

Conducted structured evaluation of digital and educational content using predefined quality criteria and scoring frameworks. Assessed clarity, coherence, relevance, usability, and comprehension, comparing alternative content versions to determine relative quality and effectiveness. Identified ambiguity, inconsistencies, missing information, weak reasoning, and unclear communication, and evaluated how well content addressed user needs in a natural, understandable way. Supported multilingual evaluation workflows while maintaining consistent quality standards and documented findings with actionable feedback for improvements.

Research & Structured Content Evaluation Associate at 4writers

January 1, 2019 - January 1, 2021

Supported AI training datasets through structured annotation, response evaluation, and quality assessment. Evaluated written outputs and model responses using guideline-based scoring and classification criteria, checking linguistic accuracy, logical consistency, relevance, clarity, and completeness. Performed comparative evaluations of multiple responses and ranked outputs according to predefined quality standards, providing documented reasoning for evaluation decisions. Identified errors, inconsistencies, and ambiguous outputs to be corrected as part of quality assurance for large-scale training projects.

Freelance Academic & Instructional Content Support Specialist at International Clients

January 1, 2018 - Present

Researched, analyzed information, and transformed complex material into clear, structured written outputs. Reviewed and refined content for accuracy, logical coherence, clarity, grammar, and audience suitability, verifying whether outputs satisfied original objectives or user requirements. Identified unsupported statements, inconsistencies, gaps in reasoning, and unclear explanations, providing concise analytical feedback and recommendations. Worked independently with client requirements, quality standards, deadlines, and revision cycles.