Michael Zellinger
AI Deployment Engineer at Artificial Advantage
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolMichael Zellinger is an AI Deployment Engineer with 8 years of experience building ML-driven products and production workflows across finance, healthcare, and scientific domains. He currently leads deployments at Artificial Advantage, translating models into business outcomes for clients in finance, real estate, advertising, and materials science. His background includes analytic and engineering roles at Oaktree, Novartis, and ETH Zürich where he accelerated macro modeling, developed semantic search with OpenAI embeddings, and improved clinical data pipelines using causal inference. Michael pairs deep quantitative training (Caltech PhD, Oxford and ETH master’s degrees, Brown ScB) with hands-on software skills—shipping React.ts/FastAPI apps and Python tooling that cut analysts’ spreadsheet work by orders of magnitude. He’s as comfortable optimizing database queries and API wrappers for speed as he is designing ML-informed UX, and he often focuses on making complex workflows measurably faster and more reproducible. Based in San Francisco, he brings a research-grade mindset to pragmatic, outcome-focused AI deployments.
8 years of coding experience
1 year of employment as a software developer
ScB, Mathematics, ScB, Mathematics at Brown UniversityMSc, Mathematical Modelling and Scientific Computing, MSc, Mathematical Modelling and Scientific Computing at University of OxfordMandarin Chinese, Mandarin Chinese at Beijing Normal UniversityCalifornia Institute of TechnologyMSc, Statistics, MSc, Statistics at ETH Zürich
German, Chinese, French, Spanish, Italian
Github Skills (15)
pytorch10
nlp10
python10
natural-language-processing10
bert9
language-model9
tensorflow9
machine-learning9
speech-recognition9
deep-learning9
transformers9
transformer9
jax8
seq2seq7
flax7
Programming languages (1)
Github contributions (5)
mzelling/entropymethod
Jan 2021 - Sep 2021
Contributions:22 commits, 6 pushes in 7 months
mzelling/repliclust
Dec 2022 - Feb 2023
Natural Language-Based Synthetic Data Generation for Cluster Analysis.
Contributions:70 commits, 2 PRs, 48 pushes in 2 months
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