Eli Bixby
Co-Founder And Senior ML Engineer at Cradle Bio
Zurich, Zurich, Switzerland
Summary
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Rockstar🎓
Top SchoolEli Bixby is a Co-Founder and Senior ML Engineer based in Zurich with 11 years of experience building production ML systems and infrastructure for biology and cloud platforms. He leads ML research and engineering at Cradle.bio, specializing in multi-round batch optimization for low-data protein design using large language models, and previously developed ML optimization techniques at Google for protein engineering and NLP products. Eli is an active open-source contributor to high-profile projects like TensorFlow and Google Cloud samples, with hands-on work improving CIFAR examples, ResNet training, and BigQuery/Cloud ML integration. He brings a rare blend of research rigor (summer research in algorithmic game theory and biophysics) and practical deployment expertise—spanning Kubernetes-based distributed training, GPU configuration, and model serving. Notably, his contributions reveal both low-level model improvements and developer-facing cloud tooling, reflecting a full-stack ML engineer comfortable from experimentation to production.
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 (38)
continuous-deployment10
google-bigquery10
kubernetes10
bigquery10
python10
machine-learning-models10
gquery10
machine-learning10
ml-deployment10
ml10
gcp10
google-cloud-storage10
mle10
api10
tensorflow10
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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