Jack Hanslope
Software Engineer at Snowflake
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolJack Hanslope is a software engineer on Snowflake’s Berlin performance team with eight years of industry experience, focused on benchmarking and driving customer-facing performance improvements. He holds a PhD in Artificial Intelligence from the University of Bristol, where his research produced new approaches to inverse reinforcement learning and applied supervised learning to improve short-term weather variable predictions. At Snowflake he translated research and tooling skills into production by designing and building benchmarking tools during his internship and now contributes to performance engineering at scale. Jack’s background blends rigorous mathematical training (MMath, Exeter) with practical analytics work from early roles at Techmodal, enabling him to bridge theoretical ML methods and real-world systems. Based in Berlin, he brings a researcher’s curiosity to production problems and an eye for measurable performance gains that directly impact customer experience. An understated strength is his ability to turn complex, low-dimensional predictive insights into pragmatic engineering solutions.
8 years of coding experience
A Levels, A Levels at York College, York UKMaster of Mathematics Mathematics, Master of Mathematics Mathematics at University of ExeterDoctor of Philosophy - PhD Artificial Intelligence, Doctor of Philosophy - PhD Artificial Intelligence at University of Bristol
Github Skills (35)
weechat8
passwords8
robotics8
simulation7
word-embeddings7
reinforcement-learning7
gnupg7
nlp7
simple-framework6
mutt6
physics6
password-manager6
natural-language-processing6
sequence-labeling6
machine-learning6
Programming languages (7)
Github contributions (5)
jackhanslope/bleu
May 2020 - Apr 2022
bleu is a bluetooth cli written in rust
Contributions:2 releases, 69 commits, 9 PRs in 1 year 10 months
rustbleulinuxbluetoothcli
jackhanslope/mlde
Sep 2023 - Jul 2024
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Contributions:36 pushes, 18 branches in 10 months
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