Eli Bixby
Co-Founder And Senior ML Engineer at Cradle Bio
Delft, South Holland, Netherlands
Summary
🤩
Rockstar🎓
Top SchoolEli Bixby is a Machine Learning Engineer based in the Netherlands with 10 years of experience building and deploying ML systems. He contributes to high-profile open-source projects such as TensorFlow and GoogleCloudPlatform, improving CIFAR/ResNet examples, GPU initialization, and training hooks while also authoring BigQuery and Cloud ML samples. At cradle.bio he blends model-development chops with infrastructure know-how—writing Kubernetes configs for distributed TensorFlow clusters, enabling TensorBoard/log management, and implementing model export and serving pipelines. That production-first mindset means he routinely moves projects from research notebooks to scalable cloud deployments.
11 years of coding experience
6 years of employment as a software developer
N/A, Mathematics, N/A, Mathematics at Budapest Semesters in MathematicsBachelor of Arts (B.A.), Mathematics and Computer Science, Chemistry, Bachelor of Arts (B.A.), Mathematics and Computer Science, Chemistry at Oberlin CollegeBachelor of Arts (B.A.), Mathematics and Computer Science, Bachelor of Arts (B.A.), Mathematics and Computer Science at Cleveland High School
Stackoverflow
1,178reputation
65kreached
18answers
4questions
tensorflow
top-5%
Github Skills (47)
continuous-deployment10
google-bigquery10
machine-learning-model10
kubernetes10
bigquery10
machinelearningmodel10
python10
machine-learning-models10
gquery10
machine-learning10
ml-deployment10
ml10
gcp10
mle10
google-cloud-storage10
Programming languages (12)
Github contributions (5)
amygdala/tensorflow-workshop
May 2016 - Jan 2017
This repo contains materials for use in a TensorFlow workshop.
Role in this project:
ML Engineer
ML EngineerContributions:102 commits, 13 PRs, 73 pushes in 8 months
Contributions summary:Eli primarily focused on integrating and configuring TensorFlow for a machine learning workshop. Their contributions include developing Kubernetes configurations for a TensorFlow cluster, including services, replication controllers, and configuration maps. They also made updates to the worker and jupyter server configurations and implemented features for tensorboard and log management, reflecting experience in distributed training infrastructure and model deployment.
workshopdeep-learningmachine-learningtensorflowtensorflow2
GoogleCloudPlatform/cloudml-samples
Oct 2016 - Sep 2017
Cloud ML Engine repo. Please visit the new Vertex AI samples repo at https://github.com/GoogleCloudPlatform/vertex-ai-samples
Role in this project:ML Engineer
ML EngineerContributions:49 commits, 11 PRs, 7 pushes in 10 months
Contributions summary:Eli contributed to the Cloud ML Engine samples repository by implementing and modifying machine learning models, specifically for iris classification and census income prediction. The commits demonstrate work on model training, evaluation, and deployment, including preprocessing steps and the use of TensorFlow. The user also worked on the creation and configuration of serving input functions and model export for deployment.
gcpcloudml-samplescloudmldeep-learninggooglecloudplatform
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