Key Skills

Software

HiveMind

Labelbox

Mindrift

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Document

Top Task Types

Computer Programming Coding

Evaluation Rating

Function Calling

Prompt Response Writing SFT

RLHF

Freelancer Overview

I am a highly motivated Data Annotation Specialist with over 3 years of experience in AI training data creation, specializing in computer vision and natural language processing tasks. I have worked with platforms such as Alingerr and Outlier, where I contributed to high-quality image, video, and text data labeling for use in machine learning model development. My work has supported projects in diverse domains, including industrial safety, educational research, and multilingual language models. I am proficient in using tools like CVAT, Labelbox, and custom in-house platforms for detailed annotations including bounding boxes, segmentation, and entity tagging. My strong technical foundation in Python, OpenCV, and data preprocessing, along with a background in chemical engineering, enables me to understand complex subject matter and deliver precise, high-volume annotations efficiently. I thrive in remote, collaborative environments and consistently uphold accuracy and consistency standards across projects.

Labeling Experience

AI Trainer

LabelboxComputer Code ProgrammingQuestion AnsweringText Generation

Worked as an AI Trainer on a large-scale project involving prompt engineering and data labeling for Gemini AI's code generation models. Collaborated with development teams to implement AI-driven solutions focused on business logic and instruction-following capabilities. Tasks included writing and evaluating Python-based prompts, classifying model responses, annotating outputs, and performing error analysis to improve model accuracy. Emphasis was placed on quality control and systematic feedback to enhance output relevance and reduce hallucinations. Project spanned thousands of code snippets and scenarios, requiring deep focus, technical consistency, and collaboration with engineers.

Worked as an AI Trainer on a large-scale project involving prompt engineering and data labeling for Gemini AI's code generation models. Collaborated with development teams to implement AI-driven solutions focused on business logic and instruction-following capabilities. Tasks included writing and evaluating Python-based prompts, classifying model responses, annotating outputs, and performing error analysis to improve model accuracy. Emphasis was placed on quality control and systematic feedback to enhance output relevance and reduce hallucinations. Project spanned thousands of code snippets and scenarios, requiring deep focus, technical consistency, and collaboration with engineers.

2024

AI Trainer

Scale AIComputer Code ProgrammingText GenerationRLHF

Worked as an AI Trainer on a large-scale STEM project, where I was responsible for annotating complex scientific data, including engineering diagrams, research texts, and experimental results. The project involved classifying technical content, annotating equations, and providing high-level entity recognition for datasets related to chemical engineering and industrial processes. I used tools like Scale AI to ensure the accuracy of scientific terminology and proper categorization of experimental data. Tasks also included labeling technical content for natural language processing (NLP) models, enhancing their ability to extract key concepts from STEM literature. The project involved extensive quality control checks and collaboration with subject-matter experts to maintain high standards of annotation precision.

Worked as an AI Trainer on a large-scale STEM project, where I was responsible for annotating complex scientific data, including engineering diagrams, research texts, and experimental results. The project involved classifying technical content, annotating equations, and providing high-level entity recognition for datasets related to chemical engineering and industrial processes. I used tools like Scale AI to ensure the accuracy of scientific terminology and proper categorization of experimental data. Tasks also included labeling technical content for natural language processing (NLP) models, enhancing their ability to extract key concepts from STEM literature. The project involved extensive quality control checks and collaboration with subject-matter experts to maintain high standards of annotation precision.

2022

Education

Work History