Hesbon J.

Key Skills

Software

Appen

Top Subject Matter

Technology & Software Development Software engineering, Python development, REST APIs, databases, algorithms, data structures, OOP

Computer Science Algorithm design, data structures, OOP, system design, debugging, code review, software engineering principles

Biological Sciences Molecular biology, genetics, cell biology, biochemistry, ecology, evolutionary biology, human physiology

Top Data Types

Audio

Top Task Types

Segmentation

Freelancer Overview

I am an experienced AI training data contributor with a proven track record across multiple platforms including Mindrift (Toloka AI), Scale AI, and Appen. My work spans data annotation, RLHF (Reinforcement Learning from Human Feedback), Python code evaluation, and domain-expert content creation across three specialized fields — Computer Science, Biology, and transcription. I have contributed thousands of validated training samples including Python code snippets, algorithm challenges, biology Q&A pairs, and scientific fact-checking tasks used directly in LLM fine-tuning pipelines. I consistently maintain quality scores of 95–99% across platforms and have earned top contributor status on Mindrift. What sets me apart is my rare combination of deep domain expertise and technical fluency. As a Computer Science graduate with advanced Python skills, I can write, debug, and evaluate code at a level that most annotators cannot — covering data structures, algorithms, OOP, APIs, and machine learning implementations. My background in Biological Sciences also allows me to handle complex scientific content with accuracy and nuance, making me a versatile contributor across STEM-focused AI projects. I am detail-oriented, deadline-driven, and deeply familiar with AI training workflows — from task onboarding and quality calibration through to batch delivery and feedback loops.

Education

Work History