Mutlu T.

Key Skills

Software

Don't disclose

Top Subject Matter

LLM evaluation and AI training data quality (reasoning, safety, instruction-following)

Data quality

predictive dataset structuring

Top Data Types

Text

Document

Top Task Types

RLHF

Freelancer Overview

Independent AI Data Consultant (Remote) — AI training support via RLHF and LLM response evaluation. Brings 12+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose and Excel. Education includes Bachelor of Science, Istanbul University (2019) and Certification, N/A. AI-training focus includes data types such as Text and labeling workflows including RLHF, Evaluation, and Rating.

Labeling Experience

Independent AI Data Consultant - Independent AI Data Consultant

TextRLHF

You execute complex AI training and evaluation tasks remotely, with an emphasis on RLHF and multi-turn dialogue assessment. You check model outputs for logical consistency, technical accuracy, nuance, and adherence to safety guidelines. You also build custom datasets focused on edge cases to improve reasoning performance for model development. • Conduct RLHF and dialogue evaluation workflows • Grade LLM outputs for accuracy and safety compliance • Perform logical consistency checking for complex responses • Design edge-case dataset content for training

2024 - Present

Independent AI Data Consultant (Remote) — AI training support via RLHF and LLM response evaluation

Don't discloseTextRLHF

Performed RLHF-oriented evaluation and grading of LLM responses for accuracy, safety, and instruction-following. Labeled outputs by assessing technical correctness, nuance, and logical consistency, with particular attention to hallucination detection. Developed and applied custom reasoning-focused criteria to stress-test model performance against edge cases. • Multi-turn dialogue evaluation and logical consistency checking • Hallucination detection, fact-checking, and logic verification • Edge-case dataset creation and labeling • Quality control to maintain adherence to strict project guidelines

2024 - Present

Data Analysis & Operations Specialist — structured data validation and quality-focused labeling

Text

Created structured datasets and performed evaluation-style labeling for predictive analysis use cases. Ensured data integrity through rigorous validation and consistency checks across large-scale records. Produced actionable insights by transforming raw structured data into high-quality outputs for downstream project development. • Large-scale data validation and integrity checks • Analytical performance modeling support using structured datasets • Consistency-focused dataset organization • Workflow streamlining to generate machine-usable insights

2015 - 2024

Education

Work History