Joseph M.

Key Skills

Software

Other

Top Subject Matter

AI data annotation and text classification

Prompt evaluation for AI-assisted annotation work

Healthcare symptom-checking (text inputs)

Top Data Types

Text

Top Task Types

Prompt + Response Writing (SFT)

Diagnosis

Freelancer Overview

Data Annotation Practice (text classification, content review, quality assessment). Core strengths include Other. Education includes Bachelor's Degree, N/A (2024). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

MedConsult AI (symptom-checking platform; annotation/QA support)

OtherTextDiagnosis

Contributed to MedConsult AI, an AI symptom-checking platform, where text-based user symptoms required careful handling for downstream interpretation. Assisted with data preparation and guideline-based review to improve reliability of symptom-related inputs and outputs. Focused on evaluating information for consistency and accuracy to support effective symptom assessment flows. • Symptom-checking related text handling for AI platform use • Quality assurance and guideline-based review of symptom inputs/outputs • Evaluation of information consistency and potential inaccuracies • Support for making structured symptom-related data usable for training/inference

2024 - Present

Prompt evaluation and quality review (AI-assisted tasks)

OtherTextPrompt + Response Writing (SFT)

Engaged in prompt evaluation and instruction-following for AI-assisted tasks as part of annotation-adjacent project work. Assessed responses against requirements to ensure outputs matched expected formats and content constraints. Helped maintain data quality by flagging mismatches, inaccuracies, and guideline violations. • Prompt evaluation and response validation against criteria • Detection of inconsistencies and incorrect or noncompliant outputs • Support for high-accuracy review workflows • Quality-focused checking to prepare outputs for downstream use

2024 - Present

Data Annotation Practice (text classification, content review, quality assessment)

OtherText

Contributed to a text classification data annotation practice by reviewing content and assessing quality against provided guidelines. Evaluated outputs for accuracy, consistency, and adherence to labeling criteria while identifying errors or ambiguous cases. Participated in iterative quality checks to improve dataset reliability and training readiness. • Text classification labeling support with guideline-based checks • Content review for quality assessment and adherence to instructions • Identification of inconsistencies and borderline/ambiguous instances • QA-focused verification to ensure labeling correctness

2024 - Present

Education

Work History