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Shari Bijaczyk

Shari Bijaczyk

AI Evaluator & Generative AI Practitioner

USA flagEwing, Usa
$30.00/hrIntermediate

Key Skills

Software

No software listed

Top Subject Matter

Generative AI/LLM evaluation
Technology, Software, and Digital Products
E-commerce-Product Categorization & Customer Support

Top Data Types

TextText
ImageImage

Top Task Types

Evaluation/RatingEvaluation/Rating
Question AnsweringQuestion Answering
Text GenerationText Generation
Red TeamingRed Teaming
Data CollectionData Collection
ClassificationClassification

Freelancer Overview

I have hands‑on experience working with generative AI in a previous role, where I supported prompt testing, reviewed model outputs, and evaluated responses for clarity and accuracy as well as automation. I also completed MIT’s Driving Innovation with Generative AI certification, which strengthened my understanding of LLM behavior, prompt design, and evaluation methods. My broader background includes 14+ years in product and technology roles that required analytical thinking, structured workflows, and quality‑focused execution — all of which translate well to AI training and evaluation tasks.

IntermediateEnglish

Labeling Experience

AI Evaluator and Generative AI Specialist

Text
As an AI Evaluator and Generative AI Specialist, I evaluated LLM model outputs for accuracy, safety, clarity, and hallucination risk. I performed structured annotation, data quality assessment, guideline-based evaluation, and prompt testing for generative AI models. Work consisted of detailed model evaluation, prompt engineering, red-teaming, and scenario-based analysis. • Evaluated model outputs for safety, accuracy, and clarity • Performed hallucination detection and prompt optimization • Conducted red-teaming, bias detection, and edge-case analysis • Used structured annotation under strict guidelines

As an AI Evaluator and Generative AI Specialist, I evaluated LLM model outputs for accuracy, safety, clarity, and hallucination risk. I performed structured annotation, data quality assessment, guideline-based evaluation, and prompt testing for generative AI models. Work consisted of detailed model evaluation, prompt engineering, red-teaming, and scenario-based analysis. • Evaluated model outputs for safety, accuracy, and clarity • Performed hallucination detection and prompt optimization • Conducted red-teaming, bias detection, and edge-case analysis • Used structured annotation under strict guidelines

2023 - Present

Education

M

MIT

Certificate, Generative Artificial Intelligence

Certificate
2024 - 2024
G

General Assembly

Certificate, User Experience Design

Certificate
2019 - 2019

Work History

J

Johnson & Johnson

Product Lead Engineer / Solution Lead

Ewing
2025 - Present
J

Johnson & Johnson

Technology Solution Lead

Ewing
2023 - 2025