Jassika Ledwani

Key Skills

Software

Remotasks

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Image

Text

Top Task Types

Computer Programming Coding

Data Collection

Prompt Response Writing SFT

Text Generation

Text Summarization

Freelancer Overview

As a seasoned annotator and data specialist, I've streamlined quality assurance for AI models through expert implementation of automation pipelines in Python and JavaScript. My hands-on experience includes creating, optimizing, and maintaining robust datasets tailored specifically for machine learning training and inference tasks. Leveraging sophisticated anomaly detection and data validation techniques, I've ensured data integrity and accuracy. Additionally, my proficiency in evaluating model responses using NLP-based ranking methodologies has directly enhanced model performance and user experience.

Labeling Experience

Senior Data Quality Annotator

Scale AIComputer Code ProgrammingText GenerationComputer Programming Coding

As a Senior Data Quality Annotator at Cohere, I worked on a large-scale AI model evaluation and data labeling project aimed at improving natural language processing (NLP) model performance and safety. The project involved curating and optimizing high-quality datasets for machine learning (ML) training and inference. My primary responsibilities included: - Data labeling and annotation: Conducted precise annotations for NLP tasks such as intent recognition, sentiment analysis, and response ranking to ensure models understood human language effectively. - Automation pipelines: Developed Python and JavaScript-based automation scripts to streamline data validation, anomaly detection, and quality control, significantly reducing manual effort. - Quality assurance: Implemented data validation techniques to identify inconsistencies, ensuring high accuracy and integrity of AI-generated responses. - Model safety and evaluation: Assessed AI model responses based

As a Senior Data Quality Annotator at Cohere, I worked on a large-scale AI model evaluation and data labeling project aimed at improving natural language processing (NLP) model performance and safety. The project involved curating and optimizing high-quality datasets for machine learning (ML) training and inference. My primary responsibilities included: - Data labeling and annotation: Conducted precise annotations for NLP tasks such as intent recognition, sentiment analysis, and response ranking to ensure models understood human language effectively. - Automation pipelines: Developed Python and JavaScript-based automation scripts to streamline data validation, anomaly detection, and quality control, significantly reducing manual effort. - Quality assurance: Implemented data validation techniques to identify inconsistencies, ensuring high accuracy and integrity of AI-generated responses. - Model safety and evaluation: Assessed AI model responses based

2023 - 2024

Education

Work History