Monica M.

Key Skills

Software

Don't disclose

Other

Top Subject Matter

AI model evaluation and RLHF for text responses across finance

Regulatory Compliance & Risk Analysis

Operations Domain Expertise

Top Data Types

Text

Document

Image

Top Task Types

RLHF

Bounding Box

Text Generation

Fine-tuning

Evaluation/Rating

Transcription

Prompt + Response Writing (SFT)

Object Detection

Freelancer Overview

AI Trainer (RLHF & Prompt Development) - Data Annotation. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose and Other. Education includes Bachelor of Science, Jomo Kenyatta University of Agriculture and Technology (2023) and Certified Investments and Financial Analyst, KASNEB (2021). AI-training focus includes data types such as Text and labeling workflows including RLHF, Evaluation, and Rating.

Labeling Experience

Finance & Budget Officer (Administrative & Compliance Operations)

OtherText

Performed data validation and compliance audits on financial reports with a strong emphasis on logical accuracy and policy adherence. Produced structured audit responses and expenditure analyses by translating complex fiscal data into stakeholder-ready documentation. Cross-checked multi-departmental workflows and budget projections to identify discrepancies and enforce data integrity. • Verified financial entries against strict policy frameworks and ensured logical consistency • Prepared regulatory submission materials with confidentiality and precision • Drafted clear audit documentation and analyses for stakeholder review • Implemented corrective tracking measures to resolve projection discrepancies

2024 - 2025

AI Trainer (RLHF & Prompt Development) - Data Annotation

Don't discloseTextRLHF

Trained and evaluated AI responses using RLHF-style output ranking and prompt testing. Built and refined multi-dimensional grading rubrics covering logical consistency, tone alignment, and instruction following. Conducted quality assurance audits across large-scale annotation batches to identify recurring model errors and improve feedback loops. • Applied structured logical reasoning to rank, compare, and validate nuanced AI responses • Developed targeted prompt-engineering strategies and corrective examples for factual accuracy • Defined “Ideal Response Profiles” across diverse user personas to ensure helpfulness and ethical alignment • Performed hallucination and logical fallacy investigation with strict guideline and cultural-sensitivity adherence

2024 - 2025

Education

Work History