Dennis G.

Key Skills

Software

Other

Scale AI

Top Subject Matter

Life sciences

scientific writing

general language

Top Data Types

Text

Top Task Types

Prompt + Response Writing (SFT)

Entity (NER) Classification

Freelancer Overview

Freelance AI Trainer & Data Annotation Specialist (Remote/Global) — Response Evaluation & RLHF. Brings 11+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other and Scale AI. Education includes Bachelor of Science, University of Eldoret (2018) and Certificate, Nairobi Institute of Business Studies (2014). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

Freelance AI Trainer & Data Annotation Specialist · Remote, Global ·

Scale AITextEntity (NER) Classification

No description provided.

2020 - Present

Freelance AI Trainer & Data Annotation Specialist · Remote — Various AI Training Projects

Scale AITextEntity (NER) Classification

No description provided.

2020 - Present

Freelance AI Trainer & Data Annotation Specialist (Remote/Global) — Text Annotation & Multilingual Language Evaluation

OtherTextEntity (NER) Classification

Performed text annotation and labeling for classification, sentiment analysis, named entity recognition (NER), topic labeling, and instruction-following evaluation. Labeled datasets for fine-tuning support, including category tagging, relevance scoring, and structured output verification against expected behaviors. Ensured label consistency across large volumes and applied quality control checks to identify and correct annotation errors. • Classification and sentiment labeling • NER and topic label tagging • Relevance scoring and output verification • Annotation QA and label consistency checks

2020 - Present

Freelance AI Trainer & Data Annotation Specialist (Remote/Global) — Prompt Engineering & Dataset Creation

OtherTextPrompt + Response Writing (SFT)

Designed adversarial, domain-specific, and edge-case prompts to probe LLM weaknesses in reasoning, factual recall, and instruction adherence. Drafted ideal or target model responses aligned to provided style guides, including expected tone, format, depth, and accuracy. Built structured multi-turn and scenario-based prompt sets to support conversational AI training datasets. • Adversarial and edge-case prompt design • Ideal response drafting per style guides • Multi-turn conversational scenario creation • Dataset-oriented prompt engineering for training

2020 - Present

Freelance AI Trainer & Data Annotation Specialist (Remote/Global) — Response Evaluation & RLHF

OtherText

Freelance AI trainer and data annotation specialist performing RLHF-style preference ranking and response evaluation on AI outputs using structured rubrics and scoring frameworks. Conducted A/B side-by-side comparisons and produced detailed written rationales for ranking decisions, including evidence-based notes tied to accuracy, helpfulness, harmlessness, and instruction following. Reviewed outputs for safety, bias, policy violations, and edge cases while validating reasoning quality, factual correctness, and logical consistency. • Preference scoring and A/B ranking decisions • Safety, bias, and policy violation detection • Reasoning quality and factual correctness checks • Coherence and instruction-following evaluation

2020 - Present

Education

Work History