Timo Ewalds is a seasoned software engineer in London with 17 years of experience building scalable systems, from founding and scaling Nexopia to contributing at DeepMind, Google and Spotify. He combines hands-on backend and infrastructure expertise — Cassandra-backed services, high-throughput caching, and productionized ML systems — with research-facing work at DeepMind on projects like AlphaStar and weather and language models. A pragmatic engineer who sold and scaled a social network to millions of users, he also improves critical open-source ML and tooling projects (notably contributions to DeepMind’s pysc2 and the widely used Tweepy streaming client). He’s comfortable across dev, ops and API design, having shipped ingestion, scoring and resilient streaming code for real-world spikes and disaster response. Timo pairs entrepreneurial instincts with academic training in electrical and computing sciences, and brings an unusual blend of product- and research-oriented engineering to sustainability-focused ML work.
17 years of coding experience
9 years of employment as a software developer
Electrical Engineering, Electrical Engineering at University of Alberta
Contributions:4 releases, 377 commits, 53 PRs in 4 years 11 months
Contributions summary:Timo made several contributions that involved improving the overall quality of the code and error messages. Their work focused on implementing a gfile stub for file access, which indicates an understanding of the underlying file system interactions. Furthermore, they fixed various shebangs, showing attention to detail and a commitment to ensuring correct operation. They also made some refactoring of core files, implying an ability to work with core project code.
StarCraft II Client - protocol definitions used to communicate with StarCraft II.
Role in this project:
DevOps Engineer & API Developer
Contributions:22 commits, 18 PRs, 2 branches in 2 years 3 months
Contributions summary:Timo primarily focused on improving and maintaining the StarCraft II client protocol definitions and associated tools. They updated the replay downloader script to enhance Python 3 compatibility, improve code cleanliness, add features like zip file extraction, and optimize error handling. Furthermore, the user implemented various updates to the proto files, including new observations, flags, and API URL changes. Their contributions streamlined the data retrieval and replay processing pipeline.
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