Bovard Doerschuk-tiberi
Engineer, LLM Evaluation
Hilo, Hawaii, United States
Summary
🤩
Rockstar🎓
Top SchoolBovard Doerschuk-tiberi is an experienced software engineer and data scientist with 12 years building scalable cloud-native systems, currently focused on LLM evaluation at Google DeepMind. He has deep full-stack and data engineering chops from leading Kaggle competitions, designing multi-cloud streaming data warehouses, and integrating ML deployment tooling like BigQuery and Vertex AI. As co-founder of the Lux AI Challenge he combines product design and community-building to surface creative AI talent—his competition attracted 900+ stars and thousands of participants. Past roles include architecting Docker-based microservices for MIT Battlecode and delivering production ML reference implementations at enterprise scale. Based in Hilo, Hawaii, he brings a rare mix of hands-on engineering, open-source collaboration, and a teacher’s instinct for growing communities and talent.
12 years of coding experience
15 years of employment as a software developer
Master of Information, Data Science, Master of Information, Data Science at UC Berkeley School of InformationBachelor of Science (B.S.), Mathematics, Computer Science, Bachelor of Science (B.S.), Mathematics, Computer Science at Montana State University-Bozeman
French
Stackoverflow
1,185reputation
90kreached
27answers
16questions
Github Skills (20)
dependency-management10
bigquery10
python10
machine-learning10
gcp10
release-management10
unit-testing9
dockers9
docker9
tensorflow9
kaggle8
rdd6
react6
jquery-file-upload6
dictionary6
Programming languages (10)
Github contributions (5)
Kaggle/kaggle-environments
Jul 2021 - Jan 2023
Role in this project:
Backend Developer
Backend DeveloperContributions:99 reviews, 71 commits, 244 PRs in 1 year 6 months
Contributions summary:Bovard primarily focused on updating the versioning of the `kaggle-environments` library, indicating involvement in release management and potentially core library maintenance. They made several commits incrementing the version number, which is crucial for tracking changes and dependencies. Furthermore, the user integrated and managed the dependency versions of external libraries, such as Lux and gfootball.
Kaggle/docker-python
Feb 2021 - May 2021
Kaggle Python docker image
Role in this project:ML Engineer
ML EngineerContributions:8 reviews, 8 commits, 17 PRs in 3 months
Contributions summary:Bovard primarily focused on integrating and testing Google Cloud Platform (GCP) services, specifically BigQuery and Vertex AI (UCAIP). The contributions involve upgrading BigQuery library versions, integrating UCAIP for model deployment, and writing unit tests to ensure compatibility between TensorFlow and BigQuery. These changes suggest a focus on building and maintaining the functionality of a Python-based Docker image designed for Kaggle, streamlining the machine learning workflow.
kagglepythondocker-imagedata-sciencedocker
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