Samuel K.

Key Skills

Software

Telus

Top Subject Matter

Computer vision/robotics AI training (household activities)

LLM output evaluation

quality assurance

Top Data Types

Video

Text

Image

Document

Top Task Types

Action Recognition

Text Summarization

Question Answering

Transcription

Evaluation/Rating

Freelancer Overview

AI Data Annotator & Labeller, Atlas Capture (2025 – Present). Brings 9+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Atlas Capture and Telus. Education includes Master of Science, N/A (2022) and Bachelor of Science, N/A (2018). AI-training focus includes data types such as Video and Text and labeling workflows including Action Recognition, Evaluation, and Rating.

Labeling Experience

AI Data Annotator & Labeller, Atlas Capture (2025 – Present)

VideoAction Recognition

Labeled and quality-checked video, image, and task-based data to support computer vision and robotics AI training. Annotated first-person perspective household activity clips by tagging objects, actions, and events within individual frames while following structured guidelines. Progressed through tiered evaluation on the Atlas Capture platform and maintained ground-truth reliability under confidentiality and data protection requirements. • Video frame-level annotation of household activities • Object, action, and event tagging within first-person clips • Guideline-compliant labeling across high-volume task queues • Tiered evaluation progression demonstrating quality consistency

2025 - Present

AI Data Annotator & Quality Evaluator, TELUS Digital (AI Community) (2024 – Present)

TelusText

Annotated and labeled multimodal content—including text, images, audio, and documents—to train machine learning models for global technology clients. Evaluated AI-generated outputs for tone, factual accuracy, grammar, and audience suitability using structured quality rubrics. Performed pairwise comparisons and helpfulness evaluations of LLM responses, applying content safety and classification guidelines to flag and categorize data accurately. • Multimodal annotation covering text-related labeling tasks • Quality evaluation of AI outputs using rubrics (tone/accuracy/grammar/audience) • Pairwise and helpfulness judgments for LLM behavior alignment • Content safety review and classification across diverse task types

2024 - Present

Education

Work History