Ben Decoste

Co-Founder at Cape

Halifax, Nova Scotia, Canada
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Summary

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Rockstar
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Top School
Ben Decoste is a Co-Founder and seasoned software engineer with 14 years of experience building backend systems, mobile tooling, and privacy-preserving ML infrastructure from Halifax, Nova Scotia. He co-founded Cape after earlier startup experience at Sidestory and a formative engineering tenure through GoInstant and Salesforce, where he worked across front-end, backend, and Android SDKs. Hands-on contributor to OpenMined’s PySyft, he’s added core tensor operations, loss functions, and grid training support—demonstrating expertise at the intersection of ML engineering and secure, distributed data science. Comfortable moving between startup execution and deep technical implementation, Ben blends product-minded leadership with contributions to open-source privacy tooling like tf-encrypted and Cape Privacy.
code14 years of coding experience
job3 years of employment as a software developer
bookBachelor of Computer Science, Bachelor of Computer Science at Dalhousie University
languagesEnglish
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Stackoverflow

Stats
788reputation
109kreached
11answers
5questions
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Github Skills (22)

pytorch10
operation10
python10
tensorrt10
machine-learning10
tensorflow10
federated-learning10
tensor10
deep-learning9
keras9
api7
apidoc7
nodejs6
aes-gcm6
tdd6

Programming languages (12)

C#TypeScriptJavaC++RustCJavaScriptGo

Github contributions (5)

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OpenMined/PySyft

Nov 2017 - Oct 2019

Perform data science on data that remains in someone else's server
Role in this project:
userBack-end Developer & ML Engineer
Contributions:82 commits, 23 PRs, 4 pushes in 1 year 11 months
Contributions summary:Ben contributed significantly to the `pysyft` repository, focusing on implementing and adding features related to tensor operations and model training. They added new functions to the `FloatTensor` class such as `zero_()`, `tanh()`, `sqrt()` and `to_numpy()` improving the tensor's functionality. They also added a `MSELoss` function to the `.nn` package and made improvements to the underlying controller, by creating its own identity. Furthermore, the user implemented the infrastructure to support grid training.
data-sciencedeep-learningsecure-computationpytorchprivacy
capeprivacy/cape

Jul 2020 - Oct 2020

Cape Core
Contributions:2 releases, 9 reviews, 50 PRs in 2 months
cape
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