Sam O.

Key Skills

Software

Label Studio

CVAT

Don't disclose

Top Subject Matter

NLP text annotation (sentiment, intent, NER)

Computer vision image annotation (object detection)

LLM response evaluation and RLHF-oriented rating

Top Data Types

Text

Image

Top Task Types

Classification

Polygon

Freelancer Overview

Data Labeling Contributor (Freelance / Self-Initiated). Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Label Studio, CVAT, and Don't disclose. Education includes Student (Self-Directed Online Learning), Self-Directed Online Learning (2023) and Online Course (In Progress), Online Learning (2024). AI-training focus includes data types such as Text and Image and labeling workflows including Classification, Polygon, and Evaluation.

Labeling Experience

Data Labeling Contributor (Freelance / Self-Initiated)

CVATImagePolygon

Labeled image datasets using bounding boxes and polygon masks to support object detection and related computer vision model training. Maintained high accuracy while applying labeling standards across sessions with minimal revision requests. Reviewed and identified edge-case imagery for senior assessment to strengthen overall training data quality. • Drew bounding boxes and polygon masks for objects • Annotated datasets for object detection model training • Ensured guideline adherence and quality assurance • Flagged ambiguous or edge cases for senior review

2024 - Present

Data Labeling Contributor (Freelance / Self-Initiated)

Label StudioTextClassification

Annotated thousands of text samples for sentiment, intent classification, and entity recognition tasks in support of machine learning training pipelines. Applied labeling guidelines consistently to maintain accuracy and minimize revisions across extended sessions. Flagged ambiguous or edge-case inputs for senior review to improve dataset quality and reliability. • Performed sentiment and intent labeling on text data • Conducted entity recognition (NER) annotation • Followed detailed guideline adherence and quality control practices • Identified and escalated ambiguous/edge cases for review

2024 - Present

AI Model Feedback Reviewer (Personal Projects)

Don't discloseText

Reviewed AI-generated outputs for correctness, tone, safety, and alignment with user intent to support personal model improvement efforts. Produced structured comparative ratings specifically for RLHF-style tasks. Documented failure patterns and bias occurrences to inform future prompt and model refinements. • Evaluated outputs for correctness, tone, safety, and intent alignment • Provided comparative ratings for RLHF tasks • Logged failure patterns and bias signals for iteration • Tested prompts across multiple LLMs to assess response quality

2023 - Present

Education

Work History