Jabir Hassan

Key Skills

Software

AWS SageMaker

Appen

Data Annotation Tech

OpenCV AI Kit (OAK)

Remotasks

Scale AI

Telus

Top Subject Matter

Image Labbeling

Text labelling

Audio Labelling

Top Data Types

Audio

Computer Code Programming

Text

Top Task Types

Audio Recording

Data Collection

Fine Tuning

Text Generation

Translation Localization

Freelancer Overview

Over the past four years, I’ve worked as a remote data labeler and AI training specialist across platforms such as Remotasks, Telus International, SWS, and Sage Manager, gaining hands-on experience in text, image, video, and audio labeling, as well as search relevance evaluation and data quality assurance. My work involves precise annotation using tools like Sage Manager, SWS, LabelBox, and Appen Connect, where I consistently maintain 98%+ accuracy while meeting strict project deadlines. I’ve developed strong skills in NER tagging, sentiment and intent classification, object detection, and speech transcription, alongside a solid understanding of how structured data fuels machine learning and AI performance. With proven efficiency, adaptability, and teamwork in remote settings, I’m passionate about ensuring data integrity that drives intelligent, reliable, and ethical AI systems.

Labeling Experience

Text Labeling (Search and NLP Projects)

Aws SagemakerTextSegmentationFine Tuning

Over the past year, I have contributed to a large-scale AI Text Understanding and Model Optimization Project with Telus International / Appen, focusing on enhancing the accuracy, coherence, and reasoning capabilities of advanced language models. The project’s scope involved improving how AI systems process human language through structured annotation, segmentation, and evaluation using SWS and Sage Manager platforms. My role centered on performing text segmentation, prompt–response creation, function-calling annotation, and fine-tuning evaluations. I labeled over 60,000+ text entries and 15,000+ prompt–response pairs across domains like education, health, and general conversation. I was responsible for analyzing complex textual data, breaking it into coherent segments, and crafting natural-sounding prompts and responses that trained the model’s understanding and generation abilities. Additionally, I annotated and reviewed function-calling data to ensure the model’s responses acc

Over the past year, I have contributed to a large-scale AI Text Understanding and Model Optimization Project with Telus International / Appen, focusing on enhancing the accuracy, coherence, and reasoning capabilities of advanced language models. The project’s scope involved improving how AI systems process human language through structured annotation, segmentation, and evaluation using SWS and Sage Manager platforms. My role centered on performing text segmentation, prompt–response creation, function-calling annotation, and fine-tuning evaluations. I labeled over 60,000+ text entries and 15,000+ prompt–response pairs across domains like education, health, and general conversation. I was responsible for analyzing complex textual data, breaking it into coherent segments, and crafting natural-sounding prompts and responses that trained the model’s understanding and generation abilities. Additionally, I annotated and reviewed function-calling data to ensure the model’s responses acc

2024 - 2025

Rater

TelusVideoClassificationObject Detection

As a rater at Telus, I played a crucial role in ensuring the quality and relevance of the company's products and services. My responsibilities included: Evaluating search results: I assessed the accuracy and relevance of search results returned by Telus's search engines, ensuring that users found the information they were looking for. Providing feedback on user experience: I shared my insights on how users interacted with Telus's products and suggested improvements to enhance their experience. Data labeling: I contributed to data labeling projects, which involved manually annotating data for use in machine learning models. This helped to improve the accuracy and efficiency of Telus's AI-powered features. Quality assurance: I helped to identify and report any issues or defects in Telus's products and services, ensuring that they met high quality standards.

As a rater at Telus, I played a crucial role in ensuring the quality and relevance of the company's products and services. My responsibilities included: Evaluating search results: I assessed the accuracy and relevance of search results returned by Telus's search engines, ensuring that users found the information they were looking for. Providing feedback on user experience: I shared my insights on how users interacted with Telus's products and suggested improvements to enhance their experience. Data labeling: I contributed to data labeling projects, which involved manually annotating data for use in machine learning models. This helped to improve the accuracy and efficiency of Telus's AI-powered features. Quality assurance: I helped to identify and report any issues or defects in Telus's products and services, ensuring that they met high quality standards.

2023 - 2024

Image and Audio labeler

Scale AIAudioClassificationText Summarization

As an audio labeler, my responsibilities included: Transcription: Accurately transcribing spoken language into written text. Speaker Identification: Identifying different speakers within audio recordings. Sound Event Detection: Locating and labeling specific sounds or events. Audio Classification: Categorizing audio clips based on content. Noise Reduction: Identifying and removing background noise. My work contributed to: Speech Recognition: Improving accuracy of speech-to-text transcription. Virtual Assistants: Enhancing capabilities of voice-activated assistants. Audio Content Analysis: Analyzing audio for tasks like copyright detection or music recommendation.

As an audio labeler, my responsibilities included: Transcription: Accurately transcribing spoken language into written text. Speaker Identification: Identifying different speakers within audio recordings. Sound Event Detection: Locating and labeling specific sounds or events. Audio Classification: Categorizing audio clips based on content. Noise Reduction: Identifying and removing background noise. My work contributed to: Speech Recognition: Improving accuracy of speech-to-text transcription. Virtual Assistants: Enhancing capabilities of voice-activated assistants. Audio Content Analysis: Analyzing audio for tasks like copyright detection or music recommendation.

2022 - 2023

Education

Work History