Taylor Joren
Machine Learning Scientist at Prescient Design
San Diego, California, United States
Summary
👤
Senior🎓
Top SchoolTaylor Joren is a Senior Machine Learning Scientist with nine years of experience applying ML to protein engineering and drug discovery, currently building LLM reasoning models and post-training environments at Genentech’s Prescient Design team. Trained at MIT in both Computer Science and Molecular Biology (BS ’19, MEng ’21), Taylor bridges computational rigor and wet-lab insight to accelerate therapeutic design. He co-created Lobster for scaling protein and molecular language-model training and invented Conditional Walk-Jump Sampling (cWJS), recognized at ICLR workshops, demonstrating a knack for practical, research-grade ML innovations. Prior roles at Sanofi and the Broad Institute include deploying scalable in silico generation pipelines that contributed to antibody discovery and building image-to-expression pipelines for single-cell analysis. Based in the Bay Area, he combines production-focused engineering with academic publishing and mentoring experience, often translating advanced models into deployed drug-discovery workflows.
8 years of coding experience
5 years of employment as a software developer
Master of Engineering - MEng, Computational Biology, Machine Learning, Master of Engineering - MEng, Computational Biology, Machine Learning at Massachusetts Institute of Technology
Github Skills (13)
plm10
protein-sequences10
biology9
issue-tracking6
anaconda4
python3
spectra3
similarity3
segment2
feature-engineering2
machine-learning2
spatial2
codebase2
Programming languages (3)
Github contributions (5)
tsorenso/BloodDVH
May 2017 - Sep 2017
Contributions:50 PRs, 124 pushes, 44 branches in 3 months
tsorenso/raman-segmentation
Jun 2020 - Jul 2020
18.065 Class Project to segment nuclei-stain images using spatial Raman spectra
Contributions:2 PRs, 101 pushes, 3 branches in 27 days
raman-spectraspatialclass-projectramansegment
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