Eric Buehler
Bioinformatics Software Engineer III
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolEric Buehler is a Bioinformatics Software Engineer III based in New York with five years of experience building reproducible, production-grade genomic workflows and data pipelines. At Memorial Sloan Kettering he extends and maintains a Django-based HPC workflow orchestrator, authors Nextflow/CWL pipelines, and manages metadata for ~8,000 samples to reduce failures in large-scale analyses. He combines strong software engineering practices (unit testing, GitHub Actions, modular Python packages) with domain expertise in variant calling and bioinformatics tooling. As an active open-source contributor to Hugging Face projects, he has implemented model integrations (including Llama 3.1 support), performance kernels, and parameter-efficient fine-tuning features like X-LoRA—bringing ML engineering rigor to both Rust and Python ecosystems. His background in data science and R/C development for large-scale education and survey data shows a pragmatic ability to translate analytic research into reliable, automated systems. Colleagues rely on him for reproducible workflows, cross-team standards adoption, and thoughtful performance improvements that aren’t obvious from job titles alone.
5 years of coding experience
6 years of employment as a software developer
Bachelor of Arts - BA, Data Analytics, Minor Computer Science, Bachelor of Arts - BA, Data Analytics, Minor Computer Science at Denison UniversityWestern Reserve AcademyCoursework, Basic Algorithms, Computer Science, Coursework, Basic Algorithms, Computer Science at New York University
Github Skills (19)
transformers10
pytorch10
integrate10
python10
machine-learning10
integrations10
llm10
adapter10
neural-network10
params10
lora10
rust10
para10
linear-algebra10
data-integration10
Programming languages (7)
Github contributions (5)
huggingface/peft
Sep 2023 - Oct 2024
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Role in this project:
ML Engineer
ML EngineerContributions:76 reviews, 7 PRs, 148 comments in 1 year 1 month
Contributions summary:Eric primarily contributed to the integration and documentation of X-LoRA, a Mixture of Low-Rank Adapter Experts, within the PEFT framework. Their work includes implementing X-LoRA's model architecture, addressing bugs related to data types, and adapting existing Lora models. They also provided examples and documentation for X-LoRA, showcasing its usage in causal language modeling scenarios.
parametermachine-learningfineparameter-efficientfine-tuning
huggingface/candle
Sep 2023 - Apr 2025
Minimalist ML framework for Rust
Role in this project:ML Engineer
ML EngineerContributions:36 reviews, 81 PRs, 283 comments in 1 year 7 months
Contributions summary:Eric implemented new methods for existing neural network layers within the framework, adding functionality like weight and bias access, as well as hidden size retrieval, improving the modularity of the library. They also addressed type casting issues within the core framework to enable upcasting integral types. Furthermore, the user added support for the Llama 3.1 model, incorporating its specific rope settings and configurations, demonstrating an ability to integrate new architectures. Lastly, the user integrated optimized Metal MLX SDPA kernels to improve performance.
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