Firdaus Abdillah

Key Skills

Software

Telus

Other

Lionbridge

Top Subject Matter

General AI

Computer Vision

Nlp Domain Expertise

Top Data Types

Image

Audio

Text

Video

Top Task Types

Object Detection

Emotion Recognition

RLHF

Entity Ner Classification

Freelancer Overview

Data Annotation in Telus Digital. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Telus, Other, and Lionbridge. Education includes Bachelor of Education, Universitas Pendidikan Indonesia (2025) and Bachelor of Education, Universitas Negeri Semarang (2021). AI-training focus includes data types such as Image, Audio, and Text and labeling workflows including Object Detection, Emotion Recognition, and RLHF.

Labeling Experience

AI Trainer in Uber AI Solutions

OtherText

Assessed side-by-side translation quality as part of AI training efforts at Uber AI Solutions in the ride-sharing and mobility sector. Evaluated translation outputs for correctness and fluency to help refine machine translation models. Reviewed and scored translation pairs for continual AI model improvement. • Compared and rated translation examples for accuracy. • Assisted in the enhancement of AI-driven language solutions. • Provided detailed feedback on machine-translated text. • Contributed to the quality enhancement of MT models.

Assessed side-by-side translation quality as part of AI training efforts at Uber AI Solutions in the ride-sharing and mobility sector. Evaluated translation outputs for correctness and fluency to help refine machine translation models. Reviewed and scored translation pairs for continual AI model improvement. • Compared and rated translation examples for accuracy. • Assisted in the enhancement of AI-driven language solutions. • Provided detailed feedback on machine-translated text. • Contributed to the quality enhancement of MT models.

2024 - Present

Data Annotator in Lionbridge

LionbridgeTextEntity Ner Classification

Engaged in data annotation and validation for various NLP projects at Lionbridge. Collected, annotated, and quality-checked text data across different tasks in accordance with established guidelines. Identified and reported inconsistencies to ensure data standard compliance. • Adhered to guidelines for consistent labeling quality. • Conducted annotation accuracy and consistency checks. • Documented results for compliance and process improvement. • Supported large-scale text data collection and annotation.

Engaged in data annotation and validation for various NLP projects at Lionbridge. Collected, annotated, and quality-checked text data across different tasks in accordance with established guidelines. Identified and reported inconsistencies to ensure data standard compliance. • Adhered to guidelines for consistent labeling quality. • Conducted annotation accuracy and consistency checks. • Documented results for compliance and process improvement. • Supported large-scale text data collection and annotation.

2025 - 2025

Annotators in e2f

OtherTextEntity Ner Classification

Annotated diverse text datasets in various languages to support robust AI model development with e2f. Ensured high accuracy and consistency in label application across multilingual, multi-domain projects. Provided feedback on guidelines to improve annotation workflows and data quality. • Worked collaboratively within a global annotation team. • Maintained strict attention to detail and met tight deadlines. • Gave process feedback for optimizing labeling efficiency. • Supported multiple languages and project types in annotation.

Annotated diverse text datasets in various languages to support robust AI model development with e2f. Ensured high accuracy and consistency in label application across multilingual, multi-domain projects. Provided feedback on guidelines to improve annotation workflows and data quality. • Worked collaboratively within a global annotation team. • Maintained strict attention to detail and met tight deadlines. • Gave process feedback for optimizing labeling efficiency. • Supported multiple languages and project types in annotation.

2025 - 2025

AI Trainer in Alignerr

OtherTextEntity Ner Classification

Worked as an AI Trainer at Alignerr focusing on the linguistic validation and data labeling for natural language processing. Provided high-quality entity classification annotations to improve NLP model accuracy. Enhanced data precision through careful review and quality control. • Annotated large volumes of text data for NLP improvements. • Performed linguistic checks and validation for model reliability. • Collaborated to refine annotation guidelines as required. • Improved the performance of AI models through detailed validation.

Worked as an AI Trainer at Alignerr focusing on the linguistic validation and data labeling for natural language processing. Provided high-quality entity classification annotations to improve NLP model accuracy. Enhanced data precision through careful review and quality control. • Annotated large volumes of text data for NLP improvements. • Performed linguistic checks and validation for model reliability. • Collaborated to refine annotation guidelines as required. • Improved the performance of AI models through detailed validation.

2025 - 2025

AI Trainer in Outlier

OtherTextRLHF

Served as an AI Trainer at Outlier synthesizing and annotating raw, unfiltered text data for unbiased datasets. Ensured all data annotations conformed to specific annotation guidelines for AI model training and evaluation. Verified, validated, and, when necessary, re-annotated data to maintain output correctness and quality. • Built well-organized datasets from raw information for AI training. • Checked AI program outputs compared to annotated examples. • Validated and re-labeled data to ensure model understanding. • Followed precise documentation and reporting standards.

Served as an AI Trainer at Outlier synthesizing and annotating raw, unfiltered text data for unbiased datasets. Ensured all data annotations conformed to specific annotation guidelines for AI model training and evaluation. Verified, validated, and, when necessary, re-annotated data to maintain output correctness and quality. • Built well-organized datasets from raw information for AI training. • Checked AI program outputs compared to annotated examples. • Validated and re-labeled data to ensure model understanding. • Followed precise documentation and reporting standards.

2024 - 2025

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Education

Work History