Rusti Rusti

Key Skills

Software

AWS SageMaker

CVAT

Data Annotation Tech

Doccano

Google Cloud Vertex AI

Labelbox

Label Studio

Prodigy

Roboflow

Snorkel AI

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Image

Text

Top Task Types

Bounding Box

Classification

Entity Ner Classification

Prompt Response Writing SFT

RLHF

Freelancer Overview

PhD in Mathematics with over 15 years of combined experience in academia, applied research, and AI training. Skilled in data labeling, annotation, and model QA evaluation across multiple domains including text, image, and audio. Proven ability to design and apply scoring rubrics, refine datasets, validate model outputs, and deliver structured feedback for improving AI performance. Experienced with leading AI training workshops and bootcamps, mentoring participants, and building learning pathways that bridge theory with real-world AI applications. Recognized for strong analytical foundations, attention to detail, and adaptability across diverse industries, from scientific QA to machine learning model evaluation. Proficient in tools such as Label Studio, CVAT, Doccano, Roboflow, and enterprise platforms like Labelbox, as well as programming in Python, R, and MATLAB. With advanced English proficiency (C1+), extensive teaching experience, and a global research background, I bring both academic rigor and practical expertise to ensure the highest quality in AI training and data evaluation projects.

Labeling Experience

LLM Evaluation and QA for Mathematics and Scientific Text

Label StudioTextEntity Ner ClassificationClassification

Conducted large-scale LLM QA and data annotation for mathematics and scientific reasoning tasks. Responsibilities included evaluating AI-generated answers, designing and applying scoring rubrics, and performing entity extraction, classification, and QA alignment checks. Annotated thousands of text samples across problem-solving, step-by-step reasoning, and scientific explanations. Ensured quality and consistency through double-review processes, peer audits, and reference validation. Provided prompt and response refinements to improve model accuracy and learning outcomes.

Conducted large-scale LLM QA and data annotation for mathematics and scientific reasoning tasks. Responsibilities included evaluating AI-generated answers, designing and applying scoring rubrics, and performing entity extraction, classification, and QA alignment checks. Annotated thousands of text samples across problem-solving, step-by-step reasoning, and scientific explanations. Ensured quality and consistency through double-review processes, peer audits, and reference validation. Provided prompt and response refinements to improve model accuracy and learning outcomes.

2021 - 2023

Image Annotation and Object Detection for Computer Vision

CVATImageBounding BoxSegmentation

Worked on a large-scale image labeling project focused on object detection and classification for computer vision applications. Tasks included creating bounding boxes and segmentation masks for thousands of images, ensuring pixel-level accuracy and consistency across datasets. Applied classification labels for multiple object categories and validated outputs against project guidelines. Maintained high quality through cross-review with peers, iterative feedback, and QC audits.

Worked on a large-scale image labeling project focused on object detection and classification for computer vision applications. Tasks included creating bounding boxes and segmentation masks for thousands of images, ensuring pixel-level accuracy and consistency across datasets. Applied classification labels for multiple object categories and validated outputs against project guidelines. Maintained high quality through cross-review with peers, iterative feedback, and QC audits.

2020 - 2021

Education

Work History