Benjamin Wilson
Principal AI FDE at Databricks
Apex, North Carolina, United States
Summary
🤩
Rockstar🎓
Top SchoolBenjamin Wilson is a Principal AI Field Data Engineer at Databricks with over a decade of experience bringing ML systems into production across e-commerce, manufacturing, and R&D. Author of Machine Learning Engineering in Action and co-host of the Adventures in Machine Learning podcast, he blends practical engineering, mentoring, and clear architecture to make AI systems simpler, safer, and easier to extend. He created the Databricks Labs automl toolkit and contributes to high-profile open-source projects like MLflow, adding model flavors and deployment improvements that help teams operationalize models. His background in nuclear and marine engineering gives him a rigorous, systems-oriented approach to root-cause investigation and statistical process control. Known for quietly removing complexity, he prioritizes reliability and reproducibility over heroics while still shipping impactful predictive models and recommendation engines. Off duty he’s spent 6+ years ensuring his dog is well-fed—evidence he’s reliable in both projects and life.
7 years of coding experience
28 years of employment as a software developer
BS Nuclear Engineering, BS Nuclear Engineering at Thomas Edison State UniversityNuclear Engineering, Nuclear Engineering at Rensselaer Polytechnic Institute
scala, apache pig, java, jmp / jsl, apache hive, sql, c#
Github Skills (7)
prophet10
machine-learning10
mlflow10
python10
documentation9
pyspark9
mlops9
Programming languages (10)
Github contributions (5)
mlflow/mlflow
Sep 2021 - Jan 2023
Open source platform for the machine learning lifecycle
Role in this project:
ML Engineer
ML EngineerContributions:22 releases, 4343 reviews, 384 commits in 1 year 4 months
Contributions summary:The user, Ben Wilson, primarily contributed to the integration and development of new features within the MLflow framework, with a focus on expanding support for machine learning models. His work included the addition of a Prophet flavor, enabling users to log and utilize Prophet models, and improvements to existing functionalities like the Spark UDF and the deployment features. Further contributions are focused on improving documentation and addressing potential issues within the codebase.
pythonlifecyclemlmachine-learningincremental-learning
BenWilson2/mlflow
Apr 2022 - Mar 2025
Open source platform for the machine learning lifecycle
Contributions:13 PRs, 843 pushes, 474 branches in 2 years 11 months
pythonmachine-learninglifecyclemachine-learning-lifecycle
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