Michael Wiest
Principal ML Engineer at Genentech
San Diego, California, United States
Summary
👤
Senior🎓
Top SchoolMichael Wiest is a Principal ML Engineer in San Diego with 8 years of experience applying deep learning and data engineering to biological problems, from single-cell phenotypic discovery to microbiome-driven agricultural insights. He has built production AI-enabled drug discovery platforms, scalable annotation tooling that enables code-free model creation for biologists, and novel time-series and hierarchical clustering methods to extract signals from terabytes of experimental data. Michael’s background spans startups and industry leaders (Spring Science, Trace Genomics, Genentech), where he has transitioned bespoke storage and analysis systems into robust Postgres-backed, web-accessible pipelines. He combines a biological engineering master’s from UC San Diego and a Princeton engineering foundation with hands-on GPU-driven model building, and he’s known for shipping practical tooling that turns complex lab workflows into consumable software. Notably, his work bridges wet lab needs and ML infrastructure—empowering scientists to explore phenotypes at scale without writing code.
9 years of coding experience
8 years of employment as a software developer
University of California, San DiegoBachelor's Degree Chemical and Biological Engineering, Bachelor's Degree Chemical and Biological Engineering at Princeton University
English, Japanese
Github Skills (15)
variable-length7
bioinformatics6
computational-biology6
python4
word2vec4
nlp3
recurrent-neural-networks3
word-embeddings3
machine-learning3
neural-network3
natural-language-processing3
godot2
simulation2
graph1
ml1
Programming languages (2)
Github contributions (5)
michaelwiest/H1rnN1
Mar 2018 - Nov 2018
Recurrent neural network for predicting protein mutations in Influenza
Contributions:40 PRs, 273 pushes, 20 branches in 8 months
recurrent-neural-networks
michaelwiest/godot-noah-game
Mar 2023 - Jun 2023
A top-down deliberately janky action RPG.
Contributions:8 reviews, 6 PRs, 34 pushes in 2 months
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