Melanie Buehler
Senior Software Engineer at Intel
Portland, Oregon, United States
Summary
👤
Senior🎓
Top SchoolMelanie Buehler is a Senior Software Engineer in Portland with 11 years of experience building production-grade software for machine learning, deep learning, and data science at Intel and earlier in analytics-focused roles. She blends hands-on ML engineering—benchmarking and serving models like ResNet50 and SSD-MobileNet for Intel’s AI Reference Models—with strong backend skills in Python, Django, SQL, and cloud/container platforms (GCP, AWS, Kubernetes). Melanie excels at translating analytic pipelines into repeatable, scalable APIs and services, optimizing heavy data workloads with careful SQL, caching, and CI practices. Her background spans research-grade statistical computing to commercial SaaS growth, and she has a talent for shrinking complex workflows into reliable, interpretable systems. Notably, she has contributed performance-focused model-serving quickstarts and benchmarks that help productionize deep learning on Intel hardware.
11 years of coding experience
15 years of employment as a software developer
Master of Science, Information Processing and Neural Networks, Master of Science, Information Processing and Neural Networks at Kings College LondonGraduate Certificate, Medical Informatics, Graduate Certificate, Medical Informatics at Oregon Health and Science UniversityBachelor of Arts, Mathematics, Bachelor of Arts, Mathematics at Oberlin College
Github Skills (7)
object-detection10
image-recognition10
machine-learning10
tensorflow10
python9
benchmark9
benchmarking9
Programming languages (6)
Github contributions (5)
intel/ai-reference-models
Dec 2018 - Oct 2022
Intel® AI Reference Models: contains Intel optimizations for running deep learning workloads on Intel® Xeon® Scalable processors and Intel® Data Center GPUs
Role in this project:
ML Engineer
ML EngineerContributions:160 commits, 1 PR, 2 branches in 3 years 11 months
Contributions summary:Melanie added and benchmarked image recognition tutorials using TensorFlow Serving, including ResNet50, and InceptionV3 models. They also incorporated object detection examples using R-FCN and SSD-MobileNet, including creating and testing related notebooks. The commits focused on setting up the model serving, testing the performance, and creating quickstart scripts for various models in the Intel AI Kit.
optimizationsprocessorstensorflowzoomodel-zoo
mhbuehler/feature_extraction
May 2015 - Jul 2018
Contributions:2 commits, 2 pushes, 1 branch in 3 years 2 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.