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Geofrey Mwangi

AI Trainer & Prompt Engineer

Kenya flagNairobi, Kenya
$10.00/hrExpertClickworkerAppenData Annotation Tech

Key Skills

Software

ClickworkerClickworker
AppenAppen
Data Annotation TechData Annotation Tech
CrowdSourceCrowdSource
DataloopDataloop
Deep SystemsDeep Systems
Google Cloud Vertex AIGoogle Cloud Vertex AI
LabelImgLabelImg
Label StudioLabel Studio
MercorMercor
Micro1
Scale AIScale AI
Snorkel AISnorkel AI

Top Subject Matter

General Domain Expertise
Automotive Systems
AI/ML Reasoning

Top Data Types

TextText
DocumentDocument
ImageImage

Top Task Types

Prompt Response Writing SFT
Object Detection
Text Generation
Evaluation Rating

Freelancer Overview

AI Trainer & Prompt Engineer. Core strengths include Internal and Proprietary Tooling. Education includes Master of Science, Torrens University (2023) and Bachelor of Science, Torrens University (2021). AI-training focus includes data types such as Text and labeling workflows including Prompt + Response Writing (SFT), Evaluation, and Rating.

ExpertEnglish

Labeling Experience

AI Trainer & Prompt Engineer

TextPrompt Response Writing SFT
Designed, developed, and evaluated structured instruction datasets and prompts for large language model (LLM) training and evaluation. Assessed AI outputs for factual accuracy, safety alignment, technical correctness, and clarity according to defined rubrics. Performed comprehensive benchmarking and qualitative error analysis to identify hallucinations, bias, and unsafe recommendations. • Developed structured instructions to enhance LLM contextual understanding • Evaluated AI-generated text for multiple quality dimensions • Collaborated with research teams to refine training data and evaluation frameworks • Supported deployment readiness by improving model output reliability

Designed, developed, and evaluated structured instruction datasets and prompts for large language model (LLM) training and evaluation. Assessed AI outputs for factual accuracy, safety alignment, technical correctness, and clarity according to defined rubrics. Performed comprehensive benchmarking and qualitative error analysis to identify hallucinations, bias, and unsafe recommendations. • Developed structured instructions to enhance LLM contextual understanding • Evaluated AI-generated text for multiple quality dimensions • Collaborated with research teams to refine training data and evaluation frameworks • Supported deployment readiness by improving model output reliability

2022 - Present

AI Evaluation & Model Assessment Specialist

Text
Applied structured evaluation rubrics to assess AI outputs for logic, factual accuracy, safety, and clarity in automotive and technical domains. Identified hallucinations, incorrect specifications, and misleading information in AI-generated responses. Conducted comparative analyses and benchmarking of AI systems for improved reliability and safety. • Performed error analysis on technical and automotive guidance • Applied domain expertise to review high-stakes output • Supported technical information safety and accuracy reviews • Benchmarked multiple AI models in automotive domain applications

Applied structured evaluation rubrics to assess AI outputs for logic, factual accuracy, safety, and clarity in automotive and technical domains. Identified hallucinations, incorrect specifications, and misleading information in AI-generated responses. Conducted comparative analyses and benchmarking of AI systems for improved reliability and safety. • Performed error analysis on technical and automotive guidance • Applied domain expertise to review high-stakes output • Supported technical information safety and accuracy reviews • Benchmarked multiple AI models in automotive domain applications

2020 - Present

Machine Learning & AI Data Specialist

Text
Built and evaluated structured text datasets used to train machine learning and natural language processing (NLP) models. Ranked and rated AI and NLP model responses for accuracy, reasoning, and contextual understanding. Conducted quality assurance and error analysis on large scale AI text datasets. • Implemented preprocessing of AI datasets using Python and ML tools • Supported RLHF and supervised training workflows • Assisted in training LLMs using reinforcement learning and human feedback • Ensured data quality for large scale AI model training tasks

Built and evaluated structured text datasets used to train machine learning and natural language processing (NLP) models. Ranked and rated AI and NLP model responses for accuracy, reasoning, and contextual understanding. Conducted quality assurance and error analysis on large scale AI text datasets. • Implemented preprocessing of AI datasets using Python and ML tools • Supported RLHF and supervised training workflows • Assisted in training LLMs using reinforcement learning and human feedback • Ensured data quality for large scale AI model training tasks

2020 - 2022

Education

T

Torrens University

Master of Science, Artificial Intelligence

Master of Science
2022 - 2023
T

Torrens University

Bachelor of Science, Computer Science

Bachelor of Science
2018 - 2021

Work History

A

APPEN

Data Annotation Specialist

REMOTE
2023 - 2024
R

REMOTASK

AI Data Annotator

REMOTE
2020 - 2020