Yusuf Emre Genc
Machine Learning / NLP engineer with research and industry experience building LLM-powered retrieval and code-generation systems, fine-tuning large language models, and deploying ML features into production applications.
About
Machine Learning / NLP engineer with research and industry experience building LLM-powered retrieval and code-generation systems, fine-tuning large language models, and deploying ML features into production applications. Completed an M.Sc. in Informatics at TUM with a focus on deep learning, NLP, and generative models, and delivered measurable gains on the RepoExec benchmark with retrieval-efficient prompting and hierarchical semantic indexing.
- 4 years' experience
- Joined October 2025
Industry experience
- Software & Internet
- Computers & Electronics
- Education
- Media & Entertainment
- Professional Services
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Work experience· 28 roles
Developed semantic-tree-based hierarchical retrieval and code generation system using LLM-based retrieval and prompt engineering techniques. Achieved 0.46 pass@5 on RepoExec benchmark (vs 0.32 baseline). Outperformed dense RAG baselines using 13× fewer LLM calls.
Developed semantic-tree-based hierarchical retrieval and code generation system using LLM-based retrieval and prompt engineering techniques. Achieved 0.46 pass@5 on RepoExec benchmark (vs 0.32 baseline). Outperformed dense RAG baselines using 13 × fewer LLM calls.
Developed semantic-tree-based hierarchical retrieval and code generation system using LLM-based retrieval and prompt engineering techniques. Achieved 0.46 pass@5 on RepoExec benchmark (vs 0.32 baseline). Outperformed dense RAG baselines using 13×fewer LLM calls.
Education· 8
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