Atech Nogen

Key Skills

Software

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Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Top Label Types

RLHF

Freelancer Overview

I am an AI Evaluation Specialist and Technical RLHF Specialist with hands-on experience in validating and annotating data for Large Language Models, including reinforcement learning from human feedback (RLHF) projects. My background in software engineering, combined with expertise in identifying logical anomalies, security vulnerabilities, and optimizing model outputs, allows me to deliver high-quality training data for advanced AI systems. I have worked extensively with modern tech stacks such as Node.js, React, and Python, and have successfully reduced hallucination rates in AI-generated outputs by engineering comprehensive testing parameters. My projects span digital voting platforms, car rental systems, and immersive digital environments, demonstrating my ability to handle complex data labeling and annotation tasks in both structured and unstructured domains. I am passionate about ensuring data integrity, accuracy, and security throughout the AI training lifecycle.

Labeling Experience

Technical RLHF Specialist & AI Evaluation Engineer (Freelance)

LabelboxComputer Code ProgrammingRLHF

As a Technical RLHF Specialist and AI Evaluation Engineer, I conducted Reinforcement Learning from Human Feedback (RLHF) on Large Language Models by Anthropic. My responsibilities included rigorous evaluation of AI-generated code and logical reasoning outputs, focusing on accuracy and edge-case handling. I developed structured testing parameters to improve the reliability of LLMs in technical tasks. • Evaluated and scored LLM outputs related to software engineering scenarios. • Validated security, logic, and accuracy in AI-generated computer code. • Designed procedures to reduce hallucinations in technical problem-solving contexts. • Contributed to iterative improvement of model performance and reliability.

As a Technical RLHF Specialist and AI Evaluation Engineer, I conducted Reinforcement Learning from Human Feedback (RLHF) on Large Language Models by Anthropic. My responsibilities included rigorous evaluation of AI-generated code and logical reasoning outputs, focusing on accuracy and edge-case handling. I developed structured testing parameters to improve the reliability of LLMs in technical tasks. • Evaluated and scored LLM outputs related to software engineering scenarios. • Validated security, logic, and accuracy in AI-generated computer code. • Designed procedures to reduce hallucinations in technical problem-solving contexts. • Contributed to iterative improvement of model performance and reliability.

2025 - 2025

Education

Work History