John Hughes
Member Of Technical Staff at Anthropic
Cambridge, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolJohn Hughes is a Cambridge-based machine learning engineer with nine years' experience building large-scale speech and alignment models, currently a Member of Technical Staff at Anthropic. He has driven production gains at Speechmatics—helping deliver Ursa with a 25% English accuracy improvement over Whisper—while leading R&D that blends self-supervised learning, generative modelling and long-tail robustness for multilingual ASR. At Anthropic he transitioned from contractor research in LLM truthfulness and adversarial robustness to a permanent role, reflecting a practical focus on defensive strategies and empirical evaluation. His background combines a first-class Master’s in Engineering from the University of Cambridge with hands-on systems work from edge IoT to CI for satellite comms. An independent alignment researcher on GitHub, he balances cutting-edge ML research with product-grade engineering to move models from experiments into reliable, real-world deployments.
9 years of coding experience
7 years of employment as a software developer
Master’s Degree, Engineering, First class, Master’s Degree, Engineering, First class at University of Cambridge
English
Github Skills (35)
transcription10
speech-to-text9
predictive9
representations9
emotion-detection9
cli8
python8
deep-learning8
gpu8
machine-learning8
speech7
audio7
vulnerability-assessment7
speech-recognition7
raspberry6
Programming languages (7)
Github contributions (5)
safety-research/safety-tooling
Jan 2025 - Apr 2025
Inference API for many LLMs and other useful tools for empirical research
Contributions:32 reviews, 28 PRs, 52 pushes in 2 months
jplhughes/dotfiles
Nov 2019 - Mar 2025
Easily deploy my zsh and tmux configuration on new machines. Includes local and remote aliases to improve workflow.
Contributions:3 PRs, 77 pushes, 1 branch in 5 years 4 months
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