Josie I.

Key Skills

Software

Internal/Proprietary Tooling

Top Subject Matter

LLM fine-tuning and RLHF for technical/domain tasks (QGIS/ParaView)

Geospatial ML QA for spatial datasets and lidar processing

Top Data Types

Text

Image

Geospatial Tiled Imagery

Top Task Types

RLHF

Mapping

Object Detection

Freelancer Overview

AI Training Contractor | Handshake AI. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Don't disclose. Education includes Bachelor of Science, University of Oregon. AI-training focus includes data types such as Text, Geospatial, and Tiled Imagery and labeling workflows including RLHF, Mapping, and Fine Tuning.

Labeling Experience

AI Training Contractor | Handshake AI

TextRLHF

Designed and evaluated training tasks for LLM fine-tuning and RLHF pipelines using structured QA methods to judge outputs against defined quality rubrics. Authored complex prompts and detailed scoring rubrics with 20+ criteria to benchmark model performance on technical, domain-specific tasks. Ensured consistency across task batches by flagging systematic errors and iterating on rubric design to improve training signal quality. • Produced annotated training inputs/outputs for an AI data operations pipeline feeding model improvement cycles • Benchmarked performance across workflows using QGIS and ParaView domain task contexts • Iterated on rubric and task definitions based on observed error patterns and quality checks • Applied QA assessment standards to maintain batch-level reliability for training data

2023 - 2026

Senior QA Engineer - Matterport

ImageRLHF

Led end-to-end delivery of an AI accessibility proof of concept partnership across a large property portfolio with a hard public launch deadline and no dedicated PM support. Prevented data loss incidents by implementing automated checks and manual QA review to stop corrupted scan and user data from reaching production. Coordinated with external labeling partners to correct systematic mislabeling and owned a multi-stage deployment process requiring strong QA, test planning, and release management skills. • Delivered time-critical PoC coordination across thousands of properties and contractor teams • Implemented safeguards to block corrupted data through automated validation and QA review • Closed the loop between vendor outputs and production model training data • Owned full deployment workflow across QA review, staging deploy, validation testing, and production rollout

2023 - 2023

QA Analyst | Enview (Vendor oversight for spatial datasets; QA of mapping-related ML pipeline)

Don't discloseMapping

Managed up to five external vendors correcting spatial datasets across an ML processing pipeline, defining quality standards and maintaining structured feedback loops. Led QA for a U.S. Air Force disaster response mapping application by validating pre- and post-disaster comparison algorithms used in active rescue planning. Built manual and automated testing processes from scratch for a geospatial data platform processing lidar datasets. • Established automated smoke-testing to support monthly production deployments and reduce manual validation overhead • Performed quality review of spatial datasets to prevent labeling/data errors reaching downstream ML use • Coordinated vendor feedback loops to correct systematic issues in mapping-related data • Extended responsibilities across QA and agile facilitation while supporting geospatial ML data QA needs

2020 - 2022

Education

Work History