Benoit Dherin
AI Research Scientist at Google
Oakland, California, United States
Summary
🤩
Rockstar🎓
Top School
Top expert inGoogle Cloud Platform Development Essentials
Benoit Dherin is an AI research scientist at Google with 12 years of experience building production-grade machine learning and MLOps systems across industry and academia. He blends deep theoretical training (PhD in Mathematical Physics from ETH Zurich) with hands-on engineering—designing containerized ML microservices, Vertex AI/TFX pipelines, and automated CI/CD for heterogeneous GPU/FPGA clusters. At Google and in popular GoogleCloudPlatform repos he has contributed end-to-end labs and notebooks (including a patent document processing demo and MLOps immersion content) that bridge learning, deployment, and reproducibility. Previous roles include leading Watson ML teams at IBM, architecting NLP-serving platforms at SurveyMonkey, and scaling recommendation and ETL pipelines in startups. Colleagues rely on him to translate complex research into robust, deployable services and to coach teams on reproducible ML practices. He’s equally comfortable deriving geometric models in research papers as he is containerizing a training workflow for Vertex AI.
12 years of coding experience
23 years of employment as a software developer
Doctor of Philosophy (PhD), Mathematical Physics, Doctor of Philosophy (PhD), Mathematical Physics at Eidgenössische Technische Hochschule ZürichMaster's degree, Mathematics, 6/6, Master's degree, Mathematics, 6/6 at University of Geneva
English, French, German, Portuguese, Dutch
Github Skills (20)
google-cloud-platform10
docker10
entity-extraction10
bigquery10
python10
scikit10
tfx10
machine-learning10
dockers10
mlops10
scikit-learn10
vertex-ai10
kubernetes9
kubernetes-pods9
tensorflow9
Programming languages (2)
Github contributions (5)
GoogleCloudPlatform/asl-ml-immersion
Nov 2020 - Dec 2022
This repos contains notebooks for the Advanced Solutions Lab: ML Immersion
Role in this project:
MLOps Engineer
MLOps EngineerContributions:1 release, 293 reviews, 266 commits in 2 years 1 month
Contributions summary:Benoit's commits primarily focus on integrating MLOps tools and content, particularly related to ML Ops implementation with TFX. The commits introduce and add content, including content for MLOps guided projects, TFX template pipelines, and Docker and Kubernetes introductions for MLOps. The work includes setting up environments, and creating new resources as well as working with datasets.
pythondata-sciencegoogle-cloud-platformimmersionmachine-learning
GoogleCloudPlatform/mlops-on-gcp
Apr 2020 - Aug 2021
Role in this project:ML Engineer
ML EngineerContributions:1 release, 47 reviews, 127 commits in 1 year 4 months
Contributions summary:Benoit added learning objectives to the lab-01.ipynb notebook, indicating an involvement in educational content creation for the repository. The user also added code differences to lab-01.ipynb, demonstrating an engagement with the practical aspects of model training, specifically focusing on creating a training and validation split with BigQuery and wrapping a machine learning model into a Docker container for training within the Vertex AI Platform. Furthermore, changes were made to lab-02.ipynb, implying the user's involvement in setting up a Vertex AI KFP pipeline.
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