Vahe Hubert

Key Skills

Software

Label Studio

Mercor

AWS SageMaker

Other

Top Subject Matter

Computer Vision

Nlp Domain Expertise

Multimodal Data

Top Data Types

Image

Audio

Text

Document

Top Task Types

Classification

Fine-tuning

Freelancer Overview

AI Data Labeling & Quality Assurance Specialist. Brings 6+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Label Studio, Mercor, and AWS SageMaker. Education includes Doctor of Philosophy, University of Alaska (2025) and Master of Science, University of California, Berkeley (2016). AI-training focus includes data types such as Image, Audio, and Text and labeling workflows including Classification, Evaluation, and Rating.

Labeling Experience

AI Model Training Specialist

Aws SagemakerTextFine Tuning

Trained and fine-tuned AI models for biological text and molecular data interpretation, primarily for healthcare analytics and genetics. Developed automated annotation workflows for biomedical datasets and deployed transcription models for improved data processing. Collaborated directly with researchers to integrate annotation results into genomic prediction projects. • Created and optimized workflows for biomedical data annotation • Fine-tuned models using biological and genetic text datasets • Deployed transcription models for data accuracy • Ensured QA and documentation for research partners

Trained and fine-tuned AI models for biological text and molecular data interpretation, primarily for healthcare analytics and genetics. Developed automated annotation workflows for biomedical datasets and deployed transcription models for improved data processing. Collaborated directly with researchers to integrate annotation results into genomic prediction projects. • Created and optimized workflows for biomedical data annotation • Fine-tuned models using biological and genetic text datasets • Deployed transcription models for data accuracy • Ensured QA and documentation for research partners

2023 - Present

AI Data Labeling & Quality Assurance Specialist

Label StudioImageClassification

Oversaw image, text, and video labeling and QA for AI and machine learning projects, ensuring high accuracy and consistency. Led process improvements in annotation workflows and guided junior labeling staff on standards and compliance. Collaborated with engineers to refine taxonomies, improving model interpretability. • Labeled over 200K+ image, text, and video samples for computer-vision/NLP tasks • Designed annotation guidelines and implemented consistency checks • Built annotation dashboards using Label Studio and AWS SageMaker • Mentored junior annotators and managed quality procedures

Oversaw image, text, and video labeling and QA for AI and machine learning projects, ensuring high accuracy and consistency. Led process improvements in annotation workflows and guided junior labeling staff on standards and compliance. Collaborated with engineers to refine taxonomies, improving model interpretability. • Labeled over 200K+ image, text, and video samples for computer-vision/NLP tasks • Designed annotation guidelines and implemented consistency checks • Built annotation dashboards using Label Studio and AWS SageMaker • Mentored junior annotators and managed quality procedures

2020 - Present

Data Annotation Expert (Contract)

MercorAudio

Conducted thorough quality audits of multimodal AI training data, focusing on audio and video sequences for model improvement. Delivered detailed scene-level reviews and edited both modalities for optimal machine learning performance. Provided English conversational training for LLMs, enhancing intention and dialogue fluency. • Quality audited video/audio datasets and validated annotation guidelines • Ensured data integrity and project specification compliance • Trained AI models on linguistic nuance and scenario-based dialogue • Supported end-to-end data preparation, annotation, and QA cycles

Conducted thorough quality audits of multimodal AI training data, focusing on audio and video sequences for model improvement. Delivered detailed scene-level reviews and edited both modalities for optimal machine learning performance. Provided English conversational training for LLMs, enhancing intention and dialogue fluency. • Quality audited video/audio datasets and validated annotation guidelines • Ensured data integrity and project specification compliance • Trained AI models on linguistic nuance and scenario-based dialogue • Supported end-to-end data preparation, annotation, and QA cycles

2022 - 2025

Research Assistant – Biology & AI Integration

OtherImageClassification

Annotated and pre-processed biological datasets supporting AI and machine learning tasks, focusing on protein structure and gene sequencing. Used scripting languages to clean and structure data, increasing process efficiency and aiding academic research. Assisted AI model validation and provided team tutoring on annotation best practices. • Handled biological datasets annotated for AI model training • Pre-processed structured data for genomics and protein research • Developed scripts for data formatting and cleaning • Supported model testing and annotation validation

Annotated and pre-processed biological datasets supporting AI and machine learning tasks, focusing on protein structure and gene sequencing. Used scripting languages to clean and structure data, increasing process efficiency and aiding academic research. Assisted AI model validation and provided team tutoring on annotation best practices. • Handled biological datasets annotated for AI model training • Pre-processed structured data for genomics and protein research • Developed scripts for data formatting and cleaning • Supported model testing and annotation validation

2018 - 2021

Biology & Data Science Associate

OtherImageClassification

Applied AI and data science for biological/ecological image data analysis, contributing to sustainability and biodiversity research workflows. Designed experiments for species identification tasks and improved image recognition model accuracy. Collaborated with cross-disciplinary scientists on model precision and software best practices for visual data. • Labeled biological and ecological image datasets for modeling • Led image recognition AI experiments for biodiversity and climate impact • Optimized workflow and data visualization processes • Supported data labeling for grant-funded research and internal reviews

Applied AI and data science for biological/ecological image data analysis, contributing to sustainability and biodiversity research workflows. Designed experiments for species identification tasks and improved image recognition model accuracy. Collaborated with cross-disciplinary scientists on model precision and software best practices for visual data. • Labeled biological and ecological image datasets for modeling • Led image recognition AI experiments for biodiversity and climate impact • Optimized workflow and data visualization processes • Supported data labeling for grant-funded research and internal reviews

2016 - 2018

Education

Work History