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AI Developer @ Posicube · building LLM agent platforms & the runtime behind them
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Posicube Inc.
Data Scientist
June 29, 2026 – Present
kr-housing-longrag-bench
June 5, 2026 – Present
Korean real-world housing long-context benchmark seed
View Projectagent-trajectory-cluster-audit-code
May 22, 2026 – Present
Reproducibility code for a multi-dataset validation protocol auditing unsupervised LLM-agent trajectory clustering claims
View Projectself-corrective-rag
March 15, 2026 – Present
Self-Corrective RAG with DSPy-based Multi-dimensional Quality Assessment
View ProjectGPT4-AI-resume
March 2, 2023 – April 10, 2023
AI end-to-end Service that writes a personalized cover letter using gpt4.
View Projecti-moti_text2image-DL_PROJECT
February 14, 2022 – April 4, 2022
텍스트를 입력하면 해당 텍스트 의미에 해당하는 적절한 이모티콘을 생성해내는 모델 개발 프로젝트
View ProjectDL-auto_code_completion
January 7, 2022 – April 4, 2022
auto_code_complete is a deep-learning based auto word-completetion program which allows you to customize it on your needs. the model for this program is one of the deep-learning NLP(Natural Language Process) model structure called 'GRU(gated recurrent unit)'.
View ProjectML-WebAPI-apartment_price_prediction_program
December 11, 2021 – April 13, 2022
machine-learning + Web API project : to predict the estimated value of apartments in the city of GwangMyung, Korea.
View ProjectML-Youtube-Revenue-Prediction-Analysis
November 9, 2021 – April 4, 2022
youtube daily estimated revenue prediction with machine-learning (tree-based models)
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and demonstrate a strong interest in various data science domains, including ML, DL, and NLP. The diversity of projects (e.g., recommendation systems, revenue prediction, code completion, text-to-image, RAG) suggests a broad curiosity and willingness to explore different areas within data science. However, the lack of team projects or detailed descriptions of collaboration makes it difficult to fully assess cultural fit in a team environment.
Soft Skills & Operational Fit
The candidate's project descriptions are concise, but lack detail regarding problem-solving approaches, team collaboration, or specific challenges overcome. This makes it difficult to assess soft skills and operational fit beyond technical contributions. The candidate has a current Data Scientist role, which aligns with the target role.