Sasisupa G.

Key Skills

Software

Don't disclose

Top Subject Matter

AI response safety

bilingual prompt evaluation

and fact-checking

Top Data Types

Text

Audio

Image

Video

Top Task Types

RLHF

Classification

Entity (NER) Classification

Freelancer Overview

AI Data Trainer & Annotator (Generalist) - AI Training & Evaluation (RLHF) (Freelance, Remote). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose. Education includes Doctor of Medicine, St. George’s University, School of Medicine (2021) and Master of Science in Counselling Psychology, Assumption University (2020). AI-training focus includes data types such as Text, Audio, and Image and labeling workflows including RLHF, Classification, and Entity (NER) Classification.

Labeling Experience

AI Content and Evaluation Consultant - Freelance

VideoRLHFEntity (NER) Classification

You provide remote AI response evaluation and content-related prompt and translation support as a generalist consultant. You review and score outputs for safety, logical coherence, and usefulness while applying bilingual expertise to detect translation and dialogue issues. The work requires careful attention to detail, analytical fact-checking, and consistent labeling and editing quality. • Evaluate and rank AI responses for safety, helpfulness, and reasoning • Design and test bilingual prompts in English and Thai • Audit answers using domain research to identify factual and subtle logical errors • Organize and improve dataset quality across multiple modalities

2026 - Present

AI Data Trainer & Annotator (Generalist) - Multi-modality Dataset Labeling (Freelance, Remote)

Don't discloseImageClassification

Labeled large multi-modal datasets to improve AI model training across different content types. Contributed to annotation efforts for text, images, video, and audio modalities as part of model development. Ensured labeled outputs were corrected and consistent enough to support downstream training objectives. • Participate in multi-modal dataset labeling (text, images, video, audio) • Support training through consistent label quality • Review and correct labeling errors • Enable improved model performance via curated datasets

2026 - Present

AI Data Trainer & Annotator (Generalist) - Speech-to-Text Annotation & Entity Recognition (Freelance, Remote)

Don't discloseAudioEntity (NER) Classification

Assisted with speech-to-text annotation tasks to support training and evaluation of audio-to-text pipelines. Contributed to entity recognition workflows by labeling relevant entities within transcribed or speech-derived content. Followed annotation guidelines to maintain accurate, high-quality labeled data for model learning. • Speech-to-text annotation support • Entity recognition labeling on spoken content transcripts • Maintain guideline-consistent entity labeling • Improve labeled audio-derived datasets for training

2026 - Present

AI Data Trainer & Annotator (Generalist) - Data Labeling & Editing (Freelance, Remote)

Don't discloseTextClassification

Labeled and edited text datasets by categorizing and tagging examples to train AI models on cultural nuances, tone of voice, and precise meaning. Identified and corrected misclassified labels to reduce annotation errors and improve model performance. Supported downstream training by ensuring consistent, high-quality labeled outputs. • Categorize and tag text data for cultural/tone/meaning signals • Correct misclassified labels and reduce annotation error rates • Ensure label consistency for training effectiveness • Improve AI model performance through quality corrections

2026 - Present

AI Data Trainer & Annotator (Generalist) - AI Training & Evaluation (RLHF) (Freelance, Remote)

Don't discloseTextRLHF

Performed AI training and evaluation tasks by reviewing, scoring, and ranking AI responses to assess safety, logicality, and helpfulness. Wrote and tested bilingual prompts in English and Thai to evaluate translation handling, dialogue flow, and creative writing behavior. Audited model outputs using research and domain knowledge to detect factual errors and subtle reasoning flaws. • Review, score, and rank AI responses for safety and quality • Bilingual prompt design and testing (English/Thai) • Fact-checking and logical flaw detection • Optimize response quality for safer, more helpful outputs

2026 - Present

Education

Work History