Amos M.

Key Skills

Software

Remotasks

Other

OneForma

Scale AI

Top Subject Matter

AI training data for NLP/LLMs

LLM conversational and instructional datasets

General and medical-related annotation datasets

Top Data Types

Text

Image

Document

Top Task Types

RLHF

Classification

Entity (NER) Classification

Freelancer Overview

Data Labeler & AI Trainer (Remote). Professional background includes roles such as Health Records and Information Management Professional. Core strengths include Remotasks, Other, and Google Sheets. Education includes Bachelor of Science, N/A. AI-training focus includes data types such as Text and Medical DICOM and labeling workflows including Evaluation, Rating, and RLHF.

Labeling Experience

AI Data Contributor & Reviewer (Remote)

OneFormaTextEntity (NER) Classification

Collected, transcribed, annotated, and evaluated linguistic and content-based datasets under platform quality thresholds. Reviewed and evaluated AI model responses for linguistic naturalness, factual correctness, and instructional clarity. Analyzed text to extract sentiment, intent, named entities, and topic categories supporting NLP model development.•Performed sentiment, intent, NER, and topic classification on text samples.•Provided feedback on model responses to improve linguistic clarity and factual accuracy.•Monitored output quality using platform dashboards and self-corrected between batches.•Collaborated asynchronously with coordinators across time zones with reliable delivery.

Present

Data Annotator (Remote)

TextClassification

Performed text, image, and structured data annotation across multiple client projects using varying annotation schemas. Verified labeled data against source material to reduce annotation error rates and improve overall dataset quality. Followed complex multi-step SOPs to consistently apply detailed instructions independently.•Annotated medical text, general knowledge, and instructional materials with consistent judgment.•Cross-checked labels against source materials to detect and correct errors.•Documented outputs in Google Sheets and Excel for traceability and review.•Applied multi-step procedures and guideline compliance for accurate dataset creation.

Present

AI Data Annotator & Quality Reviewer (Remote)

OtherTextRLHF

Annotated conversational, instructional, and domain-specific text datasets used to train and fine-tune large language models (LLMs), applying judgment on tone, intent, and factual accuracy. Reviewed and rated AI-generated responses for coherence, helpfulness, safety, and alignment with human values as part of RLHF-style pipelines. Validated datasets for completeness, correctness, and formatting compliance and assessed prompt-response pairs with written justifications. • Tone/intent/factuality annotation for conversational text • Response rating to support RLHF feedback loops • Dataset validation and formatting compliance checks • Prompt-response ranking with written rationales

Present

Data Labeler & AI Trainer (Remote)

RemotasksTextClassification

Evaluated AI-generated outputs for quality, relevance, and factual correctness using project-specific review standards. Provided structured human feedback to support model improvement cycles and ensure consistent labeling outcomes. Ensured alignment with guidelines through careful verification and documentation of findings.•Reviewed conversational and instructional text responses for coherence, helpfulness, safety, and human-values alignment.•Validated completeness, correctness, and formatting compliance before downstream use.•Assessed prompt-response pairs and produced written justifications to guide model fine-tuning decisions.•Maintained detailed annotation logs and quality reports to track progress and systemic errors.

Present

Health Records and Information Management Professional - Healthcare Facilities

Scale AIClassification

Reviewed and processed large volumes of patient medical records and clinical documentation to ensure accuracy, completeness, and compliance with institutional standards. Managed Electronic Health Records (EHR/EMR) workflows including systematic data entry, validation, and quality checks to resolve documentation discrepancies. Applied medical terminology and ICD coding principles to interpret and assess healthcare data while maintaining strict privacy and governance practices. • Digitized paper-based records into structured digital formats and validated converted data for accuracy. • Performed data quality assurance to identify inconsistencies, duplicates, and non-conforming records. • Supported medical coding by matching clinical notes to appropriate ICD classification codes. • Maintained confidentiality of patient information using HIPAA-equivalent standards.

Not specified

Education

Work History