Khaleelu Rahman

Key Skills

Software

Labelbox

Appen

Lionbridge

OneForma

Micro1

Top Subject Matter

Face Recognition / Computer Vision

NLP / Chatbots / Conversational AI

Object Detection / AI Evaluation

Top Data Types

Image

Text

Document

Top Task Types

Bounding Box

Entity Ner Classification

Classification

Text Generation

Text Summarization

RLHF

Fine Tuning

Transcription

Evaluation Rating

Data Collection

Object Detection

Freelancer Overview

I have hands-on experience in data labeling and AI training data preparation, working across both image and text datasets in real-world AI systems. At Eagle Software India Pvt Ltd, I contributed to labeling large-scale datasets for computer vision and NLP applications, including bounding box annotation for face recognition and object detection, as well as entity tagging and intent classification for chatbot systems. I also worked on data cleaning, validation, and quality checks to ensure high accuracy and consistency in training data. In addition, I have experience using tools like Labelbox and Outlier AI, where I handled annotation tasks, reviewed outputs, and maintained quality standards. My background in AI and Data Science (B.Tech, Anna University) helps me understand how labeled data directly impacts model performance. I’m comfortable working with image, video, and text data, and I focus on delivering precise, well-structured annotations that improve overall model reliability.

Labeling Experience

Freelance Data Annotation Specialist

AudioTranscription

I worked on an audio transcription and annotation project using Labelbox, where the goal was to convert spoken audio into accurate text for training speech-to-text models. My work involved listening to audio files, transcribing them precisely, and ensuring correct formatting, punctuation, and speaker clarity. I also handled cases with background noise, accents, and multiple speakers, maintaining high-quality standards. In addition to transcription, I performed quality checks and corrections to ensure consistency and accuracy across the dataset. This project helped improve my attention to detail and understanding of how high-quality labeled audio data contributes to building reliable ASR (Automatic Speech Recognition) systems.

I worked on an audio transcription and annotation project using Labelbox, where the goal was to convert spoken audio into accurate text for training speech-to-text models. My work involved listening to audio files, transcribing them precisely, and ensuring correct formatting, punctuation, and speaker clarity. I also handled cases with background noise, accents, and multiple speakers, maintaining high-quality standards. In addition to transcription, I performed quality checks and corrections to ensure consistency and accuracy across the dataset. This project helped improve my attention to detail and understanding of how high-quality labeled audio data contributes to building reliable ASR (Automatic Speech Recognition) systems.

2026 - 2026

Freelance Data Annotation Specialist

TextRLHF

I worked on a Reinforcement Learning from Human Feedback (RLHF) project focused on improving the quality of LLM responses. My role involved reviewing AI-generated outputs, comparing multiple responses, and ranking them based on factors like relevance, accuracy, clarity, and safety. I also provided detailed feedback to help fine-tune model behavior and reduce issues like hallucination or ambiguity. The project included tasks such as response evaluation, preference ranking, prompt-response analysis, and quality validation, ensuring the model aligns better with human expectations. This experience helped me develop strong skills in AI evaluation, annotation, and understanding model behavior, especially in real-world conversational use cases.

I worked on a Reinforcement Learning from Human Feedback (RLHF) project focused on improving the quality of LLM responses. My role involved reviewing AI-generated outputs, comparing multiple responses, and ranking them based on factors like relevance, accuracy, clarity, and safety. I also provided detailed feedback to help fine-tune model behavior and reduce issues like hallucination or ambiguity. The project included tasks such as response evaluation, preference ranking, prompt-response analysis, and quality validation, ensuring the model aligns better with human expectations. This experience helped me develop strong skills in AI evaluation, annotation, and understanding model behavior, especially in real-world conversational use cases.

2025 - 2026

Freelance Data Annotation Specialist

LabelboxImageBounding Box

As a freelance annotator, I performed image labeling and object detection tasks using industry-standard platforms. My responsibilities included drawing bounding boxes, classifying objects, and ensuring data quality through thorough reviews. I maintained rigorous annotation standards to support AI evaluation workflows. • Worked with Labelbox and Outlier AI for annotation tasks • Carried out detailed image and AI evaluation tasks with quality checks • Reviewed and corrected annotations to enhance dataset reliability • Delivered datasets ready for machine learning model training

As a freelance annotator, I performed image labeling and object detection tasks using industry-standard platforms. My responsibilities included drawing bounding boxes, classifying objects, and ensuring data quality through thorough reviews. I maintained rigorous annotation standards to support AI evaluation workflows. • Worked with Labelbox and Outlier AI for annotation tasks • Carried out detailed image and AI evaluation tasks with quality checks • Reviewed and corrected annotations to enhance dataset reliability • Delivered datasets ready for machine learning model training

2023 - 2024

Education

Work History