Alex Ioannides
Interim ML Engineering Tech Lead at Novo Nordisk
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolAlex Ioannides is an interim ML engineering tech lead and hands-on software engineer with 11 years’ experience building cloud-native ML systems, MLOps platforms and high-performance deep learning infrastructure. He has led small, high-performing teams at enterprises and startups—driving migrations to Vertex AI, deploying continuous-training pipelines to Kubernetes, and delivering production ML across finance, marketplaces and healthcare research. A former financial mathematician with a PhD in Computational Neuroscience, he blends rigorous probabilistic modelling and optimisation skills with practical engineering for scalable ML delivery. He co-founded an open-source MLOps startup (Bodywork) and repeatedly bridges research and product, turning Bayesian inference and deep learning experiments into auditable, production-grade features. Based in London, he’s equally at home architecting platforms and rolling up his sleeves to write the deployment scripts that make models run reliably at scale.
11 years of coding experience
15 years of employment as a software developer
MSc Theoretical Physics, MSc Theoretical Physics at Imperial College LondonBSc Physics with Astrophysics, BSc Physics with Astrophysics at King's College LondonUniversity College London
English, Greek
Stackoverflow
1,212reputation
105kreached
31answers
2questions
Github Skills (178)
probabilistic-programming10
python10
mcmc10
elasticsearch10
seldon10
visualizations10
bayesian-inference10
automated-deployment10
dplyr10
pipeline10
batch10
kubernetes10
observability10
variational-inference10
bayesian10
Programming languages (13)
Github contributions (5)
bodywork-ml/bodywork-docs
Feb 2021 - Jul 2022
Documentation for Bodywork
Contributions:48 PRs, 55 pushes, 56 branches in 1 year 4 months
pythondata-sciencemlopsmachine-learningbodywork
bodywork-ml/bodywork-ml-pipeline-project
Mar 2021 - May 2022
Deployment template for a continuous training pipeline.
Contributions:10 commits, 10 PRs, 43 pushes in 1 year 1 month
pythontrainingcontinuous-deploymentservingpipeline
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