DeepMind, Reliability Engineer, 2017 – 2019:
- Primarily a consulting role for 100+ Researchers, providing knowledge, documentation, and tooling to bridge the gap between the research workflow and Google’s Production environment.
- Also working with DeepMind’s Research Platform team and Google's machine-learning infrastructure teams to assist with conventional Production setups.
- Brought a strong focus on UX-for-engineers: tooling and APIs must start from enabling the programmer to specify their intent.
- Was also a member of DeepMind's GDPR and Security working groups.
Google, Software Engineer, 2015 – 2017:
- Worked in Ads Engineering Productivity, Google Ads’ tooling organization.
- Lots of release automation work, mostly for local client teams, as well as some Google-wide work.
Imperial College London, PhD Candidate, 2013 – 2015:
- Worked in the Multicore group, making tools to find errors in multi-threaded programs.
- Published a paper on a novel abstraction of atomic instructions that allowed checking GPU programs that used them.
- Left before completion to work full-time at Google.
Education:
- 2:1 MEng in Computing from Imperial College.
- 4 A-Levels (3 As, 1 B).
- 11 GCSEs (A* to C).