Julian Hoben
Chief Technology Officer at BantamTechnology
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolJulian Hoben is a seasoned technology leader and hands-on CTO based in London with 11 years of software engineering experience and a strong track record as a founder and project lead. He builds practical, user-focused web applications using modern stacks (React, D3, Node) and cloud platforms while also driving DevOps and CI improvements for machine learning projects, evidenced by contributions to the Shōgun repo around testing and MKL CI. As co-founder of Highlight and founding partner of Pan Objects, he pairs product instincts—supply chain, e‑commerce and digital marketing—with deep technical delivery. His background in education and literature informs clear communication and curriculum-style team training, making him effective at mentoring and cross-functional collaboration. Colleagues describe him as curious about cutting-edge frameworks yet pragmatic about shipping reliable, enjoyable software.
11 years of coding experience
CELTA, Teaching English as a Second or Foreign Language/ESL Language Instructor, CELTA, Teaching English as a Second or Foreign Language/ESL Language Instructor at Languages InternationalBachelor of Arts - BA, English Literature (British and Commonwealth), Bachelor of Arts - BA, English Literature (British and Commonwealth) at Victoria University of Wellington
Japanese, Spanish
Github Skills (10)
c-language10
cprogramming-language10
testing9
cmake9
artificial-intelligence8
machine-learning8
data-science8
continuous-integration8
cplus7
cpp7
Programming languages (7)
Github contributions (5)
shogun-toolbox/shogun
Feb 2019 - Dec 2020
Shōgun
Role in this project:
Backend & DevOps Engineer
Backend & DevOps EngineerContributions:34 reviews, 204 commits, 240 PRs in 1 year 10 months
Contributions summary:Julian primarily contributed to testing and configuration improvements within the Shōgun repository. They fixed unit tests related to FisherLDA and DotIterator, suggesting involvement in testing and debugging. They also implemented MKL CI configurations, indicating expertise in build systems and continuous integration for machine learning projects. The user also removed polykernel from swig examples and fixed a lambda.
cmakedata-sciencegunc-plus-plusmachine-learning
gf712/python-cpp
Jul 2021 - Jan 2023
Contributions:321 commits, 215 pushes, 15 branches in 1 year 6 months
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