Sylvester Wambua

Key Skills

Software

Scale AI

Appen

Telus

Remotasks

Lionbridge

Top Subject Matter

Large Language Models

AI Training

Language Model Evaluation

Top Data Types

Text

Document

Top Task Types

Prompt Response Writing SFT

Classification

Freelancer Overview

AI Trainer (Remote) | Scale AI. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Scale AI, Outlier AI, and Appen. Education includes Master of Science, University of Nairobi (2023) and Bachelor of Science, Kenyatta University (2022). AI-training focus includes data types such as Text and labeling workflows including Prompt + Response Writing (SFT), Evaluation, and Rating.

Labeling Experience

AI Trainer (Remote) | Scale AI

Scale AITextPrompt Response Writing SFT

As an AI Trainer at Scale AI, I create prompts and generate training data for large language models. My responsibilities include evaluating AI responses for both accuracy and safety while systematically identifying hallucinations, bias, and reasoning errors. I work in a fully remote setting and collaborate with an international team of professionals. • Developed high-quality prompt datasets for supervised fine-tuning (SFT) • Evaluated AI-generated outputs for clarity and factual accuracy • Applied bias and safety checks to language model outputs • Utilized internal/proprietary tooling for annotation and review

As an AI Trainer at Scale AI, I create prompts and generate training data for large language models. My responsibilities include evaluating AI responses for both accuracy and safety while systematically identifying hallucinations, bias, and reasoning errors. I work in a fully remote setting and collaborate with an international team of professionals. • Developed high-quality prompt datasets for supervised fine-tuning (SFT) • Evaluated AI-generated outputs for clarity and factual accuracy • Applied bias and safety checks to language model outputs • Utilized internal/proprietary tooling for annotation and review

2024 - Present

AI Response Evaluator (Remote) | Outlier AI

Text

As an AI Response Evaluator at Outlier AI, I reviewed and rated model-generated textual responses for a range of tasks. The role involved verifying the factual accuracy of responses through targeted research and suggesting actionable feedback for continual model improvement. Teamwork and adherence to strict evaluation guidelines were critical to performance success. • Conducted systematic comparisons of AI completions for diverse prompts • Researched external sources to check claim validity • Applied evaluation rubrics for ranking AI outputs • Used internal/proprietary tools for annotation and feedback

As an AI Response Evaluator at Outlier AI, I reviewed and rated model-generated textual responses for a range of tasks. The role involved verifying the factual accuracy of responses through targeted research and suggesting actionable feedback for continual model improvement. Teamwork and adherence to strict evaluation guidelines were critical to performance success. • Conducted systematic comparisons of AI completions for diverse prompts • Researched external sources to check claim validity • Applied evaluation rubrics for ranking AI outputs • Used internal/proprietary tools for annotation and feedback

2023 - 2024

AI Data Annotator (Remote) | TELUS International AI

TelusTextClassification

As an AI Data Annotator for TELUS International AI, I labeled textual datasets for a variety of machine learning tasks. This included performing quality checks to ensure the integrity of AI training data. The role demanded attention to detail and adherence to project-specific protocols. • Assigned text categories for intent recognition tasks • Executed data validation and quality inspection steps • Supported model training processes with labeled samples • Worked in a remote, international collaboration environment

As an AI Data Annotator for TELUS International AI, I labeled textual datasets for a variety of machine learning tasks. This included performing quality checks to ensure the integrity of AI training data. The role demanded attention to detail and adherence to project-specific protocols. • Assigned text categories for intent recognition tasks • Executed data validation and quality inspection steps • Supported model training processes with labeled samples • Worked in a remote, international collaboration environment

2022 - 2023

Data Annotation Specialist (Remote) | Appen

AppenTextClassification

Working as a Data Annotation Specialist at Appen, I produced labeled datasets for natural language processing projects. The work involved ensuring that all annotations complied strictly with project guidelines. My focus was on maintaining high data quality across diverse labeling assignments. • Classified large volumes of text data for NLP training • Followed detailed annotation protocols for accuracy • Met quality assurance benchmarks and targets • Utilized Appen's proprietary annotation platform

Working as a Data Annotation Specialist at Appen, I produced labeled datasets for natural language processing projects. The work involved ensuring that all annotations complied strictly with project guidelines. My focus was on maintaining high data quality across diverse labeling assignments. • Classified large volumes of text data for NLP training • Followed detailed annotation protocols for accuracy • Met quality assurance benchmarks and targets • Utilized Appen's proprietary annotation platform

2022 - 2023

AI Research Contributor (Remote) | Remotasks

RemotasksTextClassification

As an AI Research Contributor at Remotasks, I annotated and reviewed text datasets used in AI model training. The position focused on ensuring that labeled data accurately reflected desired classification targets and content standards. Regular reviews of AI-generated output were essential to overall quality. • Annotated text samples for use in supervised learning • Reviewed and corrected model-generated classifications • Participated in quality assurance cycles with project leads • Used Remotasks proprietary annotation tools

As an AI Research Contributor at Remotasks, I annotated and reviewed text datasets used in AI model training. The position focused on ensuring that labeled data accurately reflected desired classification targets and content standards. Regular reviews of AI-generated output were essential to overall quality. • Annotated text samples for use in supervised learning • Reviewed and corrected model-generated classifications • Participated in quality assurance cycles with project leads • Used Remotasks proprietary annotation tools

2021 - 2022

Show more

Education

Work History