Hatef Tabbakhian

Key Skills

Software

Appen

Clickworker

Label Studio

Remotasks

Toloka

Other

Internal/Proprietary Tooling

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Document

Text

Top Task Types

Evaluation Rating

Prompt Response Writing SFT

Question Answering

RLHF

Text Generation

Freelancer Overview

I am an AI data labeling and LLM evaluation specialist with hands-on experience in text annotation, response scoring, and quality control for large language models. My work focuses on assessing instruction-following accuracy, factual consistency, relevance, and safety compliance in AI-generated content. I have contributed to structured AI training workflows including prompt-response evaluation, RLHF-style feedback, entity classification, and multilingual content review. With a strong background in economics and analytical reasoning, I bring precision, attention to detail, and consistency to every task. I am particularly effective in complex text evaluation tasks involving financial, technical, and policy-related content in English, Italian, and Persian.

Labeling Experience

LLM Response Evaluation & Quality Scoring

Scale AITextQuestion AnsweringRLHF

Evaluated AI-generated responses for instruction-following accuracy, factual correctness, relevance, and safety compliance. Applied structured scoring frameworks to assess hallucinations, logical coherence, tone appropriateness, and policy adherence. Provided detailed feedback to improve model alignment and response quality under RLHF workflows.

Evaluated AI-generated responses for instruction-following accuracy, factual correctness, relevance, and safety compliance. Applied structured scoring frameworks to assess hallucinations, logical coherence, tone appropriateness, and policy adherence. Provided detailed feedback to improve model alignment and response quality under RLHF workflows.

2024 - 2025

Multilingual AI Content Annotation (EN–IT–FA)

AppenTextEntity Ner ClassificationTranslation Localization

Reviewed and annotated multilingual AI content for semantic accuracy, contextual correctness, and linguistic fluency in English, Italian, and Persian. Ensured high-quality data for translation models and multilingual content classification systems.

Reviewed and annotated multilingual AI content for semantic accuracy, contextual correctness, and linguistic fluency in English, Italian, and Persian. Ensured high-quality data for translation models and multilingual content classification systems.

2024

Education

Work History