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Key Skills

Software

Data Annotation Tech

Scale AI

Top Subject Matter

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Top Data Types

Computer Code Programming

Image

Text

Top Task Types

Classification

Evaluation Rating

RLHF

Text Generation

Freelancer Overview

I have extensive experience in AI training and data labeling, specializing in enhancing large language models (LLMs) through precise data curation, problem evaluation, and annotation. My expertise includes designing mathematical problems to improve reasoning capabilities and assessing complex challenges for AI systems. In addition to my technical expertise, I bring a strong background in linguistics and localization, with proficiency in Turkish and English. This unique combination allows me to contribute effectively to multilingual AI projects and STEM-focused data initiatives, ensuring high-quality outcomes tailored to diverse applications.

Labeling Experience

AI Trainer

Scale AITextQuestion AnsweringDiagnosis

The project involved designing and evaluating mathematical problems to test and enhance a large language model's reasoning and problem-solving capabilities. A key aspect of my role was engaging directly with the model by presenting math questions and reviewing its step-by-step responses. I evaluated and rated each step for both calculation accuracy and reasoning quality. When errors were identified, I provided corrections and prompted the model to restart from the first mistake, ensuring iterative learning and refinement. This approach contributed to improving the model's ability to effectively tackle complex mathematical challenges with enhanced precision and reasoning.

The project involved designing and evaluating mathematical problems to test and enhance a large language model's reasoning and problem-solving capabilities. A key aspect of my role was engaging directly with the model by presenting math questions and reviewing its step-by-step responses. I evaluated and rated each step for both calculation accuracy and reasoning quality. When errors were identified, I provided corrections and prompted the model to restart from the first mistake, ensuring iterative learning and refinement. This approach contributed to improving the model's ability to effectively tackle complex mathematical challenges with enhanced precision and reasoning.

2024

AI Training Specialist

Data Annotation TechTextRLHFFine Tuning

The project involved designing and evaluating complex mathematical problems to test and improve the reasoning abilities of a large language model. Tasks included creating diverse problem sets, reviewing and validating evaluations conducted by other trainers, and providing feedback to ensure consistent quality. The scope was extensive, with a focus on refining the model's ability to solve intricate challenges across multiple mathematical domains. Quality measures adhered to included strict evaluation guidelines, thorough validations, and alignment with project standards to maintain accuracy and consistency.

The project involved designing and evaluating complex mathematical problems to test and improve the reasoning abilities of a large language model. Tasks included creating diverse problem sets, reviewing and validating evaluations conducted by other trainers, and providing feedback to ensure consistent quality. The scope was extensive, with a focus on refining the model's ability to solve intricate challenges across multiple mathematical domains. Quality measures adhered to included strict evaluation guidelines, thorough validations, and alignment with project standards to maintain accuracy and consistency.

2024

Education

Work History