Lillian S.

Key Skills

Software

Other

Internal/Proprietary Tooling

Top Subject Matter

Healthcare

Medical Records and Patient Data

Education and E-Learning

Top Data Types

Text

Document

Computer Code Programming

Top Task Types

RLHF

Text Generation

Question Answering

Freelancer Overview

My background is primarily clinical, but I have hands on experience building and deploying AI assisted website applications using multiple systems and API networks. As a PA Student Organization President at UC San Diego, I independently developed and launched a full stack web application for student utilization. This platform functions as a study tool, shared calendar, simulation tool, messaging platform, and social media style platform utilizing Supabase and Netlify. This required iterating prompts, evaluating AI outputs for accuracy and usefulness, and providing specific instruction to modify the programs reliability to produce the desired result. This workflow, I believe, closely mimics AI training and data labeling pipelines. What sets me apart from others is the wide breadth of knowledge in various disciplines from using machine learning for drug development in my research, my extensive clinical background, and passion for modulating AI to work optimally. I understand the medical side of information, while also identifying incomplete, misleading, and subtle errors in AI outputs. My dual fluency affords generation of high quality training data, annotation with nuance, and flagging edge cases that non-clinician or experienced reviewers would miss.

Labeling Experience

AI Powered Healthcare Learning Platform: Development and Prompt Engineering

TextRLHF

Independently designed and deployed a full-stack web application for a PA school cohort using coding platforms and API. The project involved iterative prompt engineering writing, evaluating, and refining AI-generated outputs to produce accurate, structured medical education content including flashcards, OSCE simulations, and clinical scenario tools. Developed hands-on fluency in identifying model limitations, correcting hallucinated or incomplete outputs, and optimizing instructions to improve response reliability core skills in AI training data workflows. Applied domain expertise in pharmacology, clinical reasoning, and medical terminology to assess output quality from a subject-matter expert perspective

2026 - Present

Education

Work History