Hamish Tomlinson
Staff Research Engineer at Google DeepMind
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolHamish Tomlinson is a Staff Research Engineer with nine years' experience applying machine learning to healthcare and life sciences, currently leading AlphaFold server engineering at DeepMind. He combines DPhil-level research rigor (Oxford, Rhodes Scholar) with hands-on ML engineering across Jax, PyTorch, TensorFlow and high-performance tooling like JIT/Numba, pyspark and Kubernetes to deliver reproducible, production-ready science. Previously a tech lead and product owner at BenevolentAI, he built and maintained multiple Python biomedical packages while driving reliability, testing and CI practices. He contributes to prominent open-source projects—having improved AlphaFold Colab performance and dependency robustness—and routinely bridges statistical genetics, deep learning and cloud ops. Colleagues value him for pragmatic technical leadership that accelerates research-to-production impact.
9 years of coding experience
7 years of employment as a software developer
DPhil Engineering Science, DPhil Engineering Science at University of OxfordBachelor of Engineering (B.E.) Mechanical Engineering, Bachelor of Engineering (B.E.) Mechanical Engineering at University of CanterburyJames Hargest College
Github Skills (8)
machine-learning10
jax10
python10
bump9
bumpversion9
versioning9
bump2version9
tensorflow7
Programming languages (1)
Github contributions (5)
google-deepmind/alphafold
Aug 2022 - Jan 2023
Open source code for AlphaFold 2.
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 10 commits, 2 PRs in 4 months
Contributions summary:Hamish primarily contributed to the AlphaFold repository by modifying the Colab notebook, fixing minor implementation details, and updating dependencies. They made changes to improve GPU utilization in relaxation steps and added version bumps and documentation updates. Further modifications included code to update the software version used in the notebook and remove a Keras dependency to resolve a potential initialization issue.
alphafold
Htomlinson14/apnea_dev
Jan 2017 - Mar 2017
Contributions:18 pushes in 1 month
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