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# Furkan Celtik

**Headline:** Professional profile
**Location:** Union City, NJ, USA

## About

Furkan Celtik is an AI developer focused on building practical AI and machine-learning systems, most recently an end-to-end document-parsing pipeline for semi-structured PDFs. Furkan combines hands-on LLM engineering and document-parsing experience with the ability to lead technical decisions, evaluate engineering trade-offs, and communicate those choices clearly to sponsors and stakeholders. Furkan recently completed a master’s degree and is motivated to turn AI research into real-world impact while staying current with evolving AI/ML technologies. In the recent document-parsing project, Furkan addressed difficult cross-page and multi-column layouts and achieved 85–90% accuracy through a pragmatic approach to technical trade-offs. Furkan values collaboration with senior engineers and prefers larger teams where different mindsets and ideas can inform stronger technical work.

## Highlights

- Built an end-to-end LLM document-parsing pipeline for semi-structured PDFs.
- Achieved 85–90% accuracy in semi-structured PDF document parsing.
- Addressed difficult cross-page and multi-column document-layout challenges.
- Made pragmatic engineering trade-offs to balance accuracy and implementation needs.
- Owned difficult technical decisions and led stakeholder and sponsor approval for technical trade-offs.
- Brings hands-on experience in LLM engineering and document parsing.
- Recently completed a master’s degree.

## FAQ

### What does Furkan do?

Furkan is an AI developer with hands-on experience in LLM engineering and document parsing. Furkan builds end-to-end pipelines for semi-structured PDF documents and contributes to technical decision-making, engineering trade-offs, and stakeholder communication.

### What was Furkan’s most recent project?

Furkan’s recent project was an end-to-end document-parsing pipeline for semi-structured PDFs. The work used LLM engineering and addressed complex document structures, including content that crossed pages and multi-column layouts.

### What accuracy did Furkan achieve in document parsing?

Furkan achieved 85–90% accuracy in the semi-structured PDF document-parsing pipeline.

### What technical challenges did Furkan address in the PDF pipeline?

Cross-page content and column-based layouts were key challenges in Furkan’s document-parsing work. Furkan made pragmatic engineering trade-offs to address those challenges while delivering 85–90% accuracy.

### What are Furkan’s strengths in technical leadership?

Furkan has demonstrated the ability to own difficult technical decisions, assess engineering trade-offs, and lead stakeholders and sponsors through approval of those decisions.

### What is Furkan’s educational background?

Furkan recently completed a master’s degree.

### What kind of team environment does Furkan prefer?

Furkan aims to stay current with AI/ML technologies, learn from senior engineers, and collaborate on work that turns AI research into impact. Furkan prefers larger teams because they offer exposure to diverse ideas and mindsets.

## Links

- LinkedIn: https://www.linkedin.com/in/furkan-enes-celtik

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