Jacob Silterra
Senior Applied AI ML Engineer at TetraScience
Greater Boston United States
Summary
🤩
Rockstar🎓
Top SchoolJacob Silterra is a Senior Applied AI/ML Engineer with 14 years of experience at the intersection of computational biology and production machine learning, now based in Greater Boston. He has driven deployment-grade deep learning for life sciences—helping deliver AlphaFold3-level structure prediction at MIT Jameel Clinic and productionizing cancer risk CNNs and diffusion GNNs—while also building single-cell TCR analysis pipelines and vector databases at Repertoire. His background spans hands-on software engineering (long-term contributor to IGV) and scientific research across genomics, qPCR diagnostics, and RNA-seq at Broad and Foundation Medicine. Comfortable moving models from research to clinical and product settings, he blends algorithmic innovation (continuous wavelet peak-finding contributions to SciPy) with pragmatic engineering: CI, refactors, and UI/UX fixes. Colleagues rely on him to translate clinician needs into deployable ML systems and to evaluate novel model architectures against real biological datasets. He holds a master’s in Biomathematics/Bioinformatics and a BS in Applied and Engineering Physics, a mix that explains his fluency across physics, biology, and scalable software.
14 years of coding experience
13 years of employment as a software developer
Bachelor of Science (B.S.), Applied and Engineering Physics, Bachelor of Science (B.S.), Applied and Engineering Physics at Cornell UniversityMaster's degree, Biomathematics, Bioinformatics, and Computational Biology, Master's degree, Biomathematics, Bioinformatics, and Computational Biology at Boston University
Github Skills (15)
javas10
bioinformatics10
algorithms10
debug10
scipy10
front-end-development10
python10
scientific-computing10
java10
numpy10
data-analysis9
ui-design9
interface-design9
user-interface9
refactoring8
Programming languages (7)
Github contributions (5)
igvteam/igv
May 2012 - Jan 2014
Integrative Genomics Viewer. Fast, efficient, scalable visualization tool for genomics data and annotations
Role in this project:
Java Developer
Java DeveloperContributions:44 commits in 1 year 7 months
Contributions summary:Jacob primarily focused on improving the user interface and fixing bugs related to the Integrative Genomics Viewer. Their contributions included making the GenomeSelectionDialog text non-editable, adding ellipses to menu items, and fixing issues related to window resizing. They also made several changes to the underlying code, including updating libraries, refactoring code for platform independence, and improving the overall functionality of the viewer. These changes indicate a focus on maintaining and improving the software's usability and stability.
scalableannotationsgenomics-datagenomicsbioinformatics
scipy/scipy
Sep 2011 - Dec 2011
SciPy library main repository
Role in this project:Data Scientist
Data ScientistContributions:14 commits in 2 months
Contributions summary:Jacob primarily contributed to the `scipy/scipy` repository by implementing and enhancing functions related to peak finding in signals. They added the `find_peaks`, `identify_ridge_lines`, and `filter_ridge_lines` functions, which use continuous wavelet transforms to locate peaks. Further, the user modified docstrings, added examples, and corrected PEP8 formatting, improving the readability and usability of the code.
scipypythonscientific-computing
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