Cheruiyot K.

Key Skills

Software

Appen

CrowdSource

Data Annotation Tech

iMerit

Mercor

Mindrift

OneForma

Remotasks

SuperAnnotate

Toloka

Telus

Top Subject Matter

AI chess game development

RLHF-style preference/ranking for model training

AI-generated code/technical content evaluation and instruction-following QA

Top Data Types

Text

Image

Video

Top Task Types

RLHF

Text Generation

Text Summarization

Transcription

Data Collection

Computer Programming/Coding

Object Detection

Polyline

Classification

Polygon

Bounding Box

Freelancer Overview

AI Chess Game Developer (Self-Employed). Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Stockfish engine, Maia chess AI, and Lc0. AI-training focus includes data types such as Computer Code and Programming and labeling workflows including RLHF, Evaluation, and Rating.

Labeling Experience

AI Chess Game Developer (Self-Employed)

RLHF

They evaluated and ranked AI chess move outputs using structured criteria to assess quality, accuracy, and strategic soundness, aligning with RLHF-style ranking and preference learning. They performed quality assurance on AI-generated moves by verifying correctness against chess logic and engine evaluations. They created structured training-ready data inputs and outputs to support downstream model training and annotation workflows. • Ranked AI move outputs for quality and strategic soundness. • Applied comparative judgments and instruction/rule-following quality checks. • Validated correctness against chess logic and engine evaluations. • Produced structured prompt/data formats for AI training workflows.

2024 - Present

Freelance Software Developer

They reviewed and validated AI-generated code and technical content for accuracy and instruction-following, performing systematic checks consistent with model evaluation. They followed detailed technical specifications and documentation standards to ensure outputs met expected requirements. This work supported quality assurance processes for AI-produced artifacts that require consistent evaluation criteria. • Assessed AI-generated code and technical content for correctness. • Checked outputs for adherence to given instructions/specifications. • Followed documentation standards and technical requirements. • Used version control practices to support iterative validation.

2023 - Present

Work History