Joel Hodgson
CEO & Co-Founder at Trubrics
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolJoel Hodgson is a founder and CEO with 7 years of experience building AI and MLOps solutions, currently leading Trubrics to deliver AI automation and behavioral insights for enterprise LLM products. Previously at Seldon he blended technical and commercial roles—contributing MLOps engineering work (including a GPU TensorFlow example integrated into Seldon Core and GKE deployments) while enabling customers to deploy and operationalize models at scale. With an engineering MEng from the University of Bath and hands-on internships at Dyson, he brings systems-thinking across hardware, test automation and cloud-native ML infrastructure. Joel pairs product-first leadership with practical engineering chops, able to move from low-level deployment details (CUDA/cuDNN, ingress, monitoring) to enterprise GTM and customer value. He’s London-based and known for translating complex ML workflows into usable, monitored systems that drive measurable efficiencies.
6 years of coding experience
Integrated Mechanical and Electrical Engineering (MEng) Engineering, Integrated Mechanical and Electrical Engineering (MEng) Engineering at University of Bath
Github Skills (11)
kubernetes10
g10
machine-learning10
deploying10
mlops10
tensorflow10
kubernetes-pods10
python9
docker8
dockers8
serve7
Programming languages (3)
Github contributions (5)
SeldonIO/seldon-core
Jun 2019 - Dec 2019
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Role in this project:
MLOps Engineer
MLOps EngineerContributions:35 commits, 12 PRs, 13 pushes in 6 months
Contributions summary:Joel's contributions primarily involve setting up and documenting a Tensorflow GPU MNIST example within the Seldon Core framework. They integrated the GPU-enabled Tensorflow example, including the installation of necessary dependencies like CUDA and cuDNN. The user also added documentation and example files, and integrated the example into a GKE deployment using Seldon Core, which included setting up ingress and testing.
monitorservingdata-sciencedeploymentmachine-learning
JoelH96/seldon-core
Jun 2019 - Dec 2019
Machine Learning Deployment for Kubernetes
Contributions:2 PRs, 15 pushes, 5 branches in 5 months
deploymentmachine-learningmlopskubernetestensorflow
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