Noah Owens Abuto Odongo

Key Skills

Software

Scale AI

AWS SageMaker

Toloka

Remotasks

Prodigy

Mindrift

Labelbox

Data Annotation Tech

Top Subject Matter

Large language models and machine learning system evaluation

LLM evaluation and prompt engineering

Legal Services & Contract Review

Top Data Types

Document

Geospatial Tiled Imagery

Computer Code Programming

Top Task Types

RLHF

Computer Programming Coding

Prompt Response Writing SFT

Red Teaming

Data Collection

Polygon

Bounding Box

Segmentation

Classification

Entity Ner Classification

Point Key Point

Object Detection

Question Answering

Text Generation

Polyline

Cuboid

Evaluation Rating

Fine Tuning

Text Summarization

Function Calling

Transcription

Freelancer Overview

AI Data Annotation & Model Evaluation Specialist. Brings 5+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Scale AI, Labelbox, and Alignerr. Education includes Doctor of Philosophy, Massachusetts Institute of Technology (2024) and Master of Science, Massachusetts Institute of Technology (2021). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI Data Annotation & Model Evaluation Specialist

Scale AIComputer Code ProgrammingComputer Programming Coding

I supported large language model evaluation and training by generating prompts, reviewing responses, and annotating outputs. My work involved quality assurance for datasets and adhering to structured annotation guidelines for model training. I contributed to prompt testing workflows and collaborated with teams to refine annotation standards. • Labeled and reviewed model-generated text responses for accuracy and consistency. • Created evaluation prompts to assess model output reasoning. • Conducted quality checks on annotated datasets. • Used multiple industry-leading AI training platforms including Scale AI and Labelbox.

I supported large language model evaluation and training by generating prompts, reviewing responses, and annotating outputs. My work involved quality assurance for datasets and adhering to structured annotation guidelines for model training. I contributed to prompt testing workflows and collaborated with teams to refine annotation standards. • Labeled and reviewed model-generated text responses for accuracy and consistency. • Created evaluation prompts to assess model output reasoning. • Conducted quality checks on annotated datasets. • Used multiple industry-leading AI training platforms including Scale AI and Labelbox.

2023 - Present

LLM Evaluation Workflow Contributor

Geospatial Tiled ImageryComputer Programming Coding

I participated in workflows evaluating the reasoning accuracy of large language models. My responsibilities included developing structured prompts and labeling model outputs to improve training datasets. I supported model response evaluation and helped design the annotation process. • Developed and tested prompts for LLM evaluation. • Labeled outputs for model training and assessment. • Ensured high-quality training data through structured annotation. • Worked closely with research and engineering teams during evaluation cycles.

I participated in workflows evaluating the reasoning accuracy of large language models. My responsibilities included developing structured prompts and labeling model outputs to improve training datasets. I supported model response evaluation and helped design the annotation process. • Developed and tested prompts for LLM evaluation. • Labeled outputs for model training and assessment. • Ensured high-quality training data through structured annotation. • Worked closely with research and engineering teams during evaluation cycles.

2023 - 2024

Education

Work History