Sutris No

Key Skills

Software

Appen

Clickworker

CrowdSource

CVAT

Labelbox

Lionbridge

OneForma

Remotasks

Scale AI

Toloka

Telus

VoTT

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Audio Recording

Classification

Data Collection

Evaluation Rating

Translation Localization

Freelancer Overview

I have over two years of experience in data evaluation and AI training data, primarily as a Search Engine Evaluator at Telus International. In this role, I assessed and improved search engine results for relevance, accuracy, and overall user experience. My work contributed directly to refining AI algorithms, ensuring high-quality and contextually accurate outputs. With a Bachelor’s degree in Computer Engineering and strong technical proficiency in Microsoft Office tools and Adobe Photoshop, I bring both analytical and creative skills to AI training data projects. My adaptability, responsibility, and commitment enable me to work effectively in both independent and team-based environments, making me a reliable contributor to high-precision data labeling and evaluation tasks.

Labeling Experience

Search Engine Evaluation & AI Training Data Annotation

TelusTextClassificationTranslation Localization

Participated in a large-scale AI training and evaluation project for a major technology client. Tasks included reviewing, classifying, and rating search engine results for accuracy, relevance, and quality; evaluating translated text for linguistic and contextual correctness; and providing detailed feedback to improve AI-generated content. The project involved processing hundreds of daily tasks while adhering to strict quality guidelines, deadlines, and performance metrics. Consistently maintained accuracy scores above the client’s threshold to ensure high-quality training data for machine learning models.

Participated in a large-scale AI training and evaluation project for a major technology client. Tasks included reviewing, classifying, and rating search engine results for accuracy, relevance, and quality; evaluating translated text for linguistic and contextual correctness; and providing detailed feedback to improve AI-generated content. The project involved processing hundreds of daily tasks while adhering to strict quality guidelines, deadlines, and performance metrics. Consistently maintained accuracy scores above the client’s threshold to ensure high-quality training data for machine learning models.

2022 - 2025

Video Annotation Project – Appen (SRT Tool)

AppenVideoClassificationObject Detection

Conducted video annotation tasks using the SRT platform to support AI model training. Responsibilities included identifying and classifying objects, tracking object movement across frames, and annotating specific actions or events. Ensured accuracy and consistency in labeling by following detailed project guidelines and performing quality checks. Delivered annotations for thousands of video segments, meeting strict productivity and accuracy benchmarks to support computer vision and action recognition projects.

Conducted video annotation tasks using the SRT platform to support AI model training. Responsibilities included identifying and classifying objects, tracking object movement across frames, and annotating specific actions or events. Ensured accuracy and consistency in labeling by following detailed project guidelines and performing quality checks. Delivered annotations for thousands of video segments, meeting strict productivity and accuracy benchmarks to support computer vision and action recognition projects.

2022 - 2024

Image Annotation Project – Appen (EWOQ Tool)

AppenImageBounding BoxClassification

Performed large-scale image annotation tasks for an AI training dataset using the EWOQ platform. Responsibilities included identifying and labeling objects within images using bounding boxes, classifying images into predefined categories, and ensuring annotation accuracy based on detailed project guidelines. Maintained high quality through regular review and correction cycles, meeting both productivity and accuracy targets. Contributed to the development of computer vision models by delivering precise and consistent annotations across thousands of images.

Performed large-scale image annotation tasks for an AI training dataset using the EWOQ platform. Responsibilities included identifying and labeling objects within images using bounding boxes, classifying images into predefined categories, and ensuring annotation accuracy based on detailed project guidelines. Maintained high quality through regular review and correction cycles, meeting both productivity and accuracy targets. Contributed to the development of computer vision models by delivering precise and consistent annotations across thousands of images.

2020 - 2021

Education

Work History