William Hirst
ML Engineer Project Owner at Elliptic Labs
Oslo, Norway
Summary
🤩
Rockstar🎓
Top SchoolWilliam Hirst is a Machine Learning Engineer based in Oslo with six years of experience applying physics-rooted computational science to real-world ML products. Currently at Elliptic Labs, he blends research-grade rigor with product delivery, and previously contributed to the ivy project—helping convert ML code across frameworks and implementing linear algebra primitives to improve cross-backend compatibility. His background includes hands-on forecasting and data engineering work at Heimdall Power and community-facing roles at Ivy, where he both extended codebase features and maintained outreach. Comfortable at the intersection of research, open source, and product engineering, he brings a physics-trained analytical mindset to building robust, framework-agnostic ML tooling.
6 years of coding experience
4 years of employment as a software developer
Master's degree, Computational Science: Physics, Master's degree, Computational Science: Physics at University of Oslo
Github Skills (11)
pytorch10
machine-learning10
python10
linear-algebra10
converter10
numpy10
jax9
deeplearning-ai9
deep-learning9
testing8
tensorflow8
Programming languages (2)
Github contributions (5)
unifyai/ivy
Sep 2022 - Dec 2022
Convert Machine Learning Code Between Frameworks
Role in this project:
ML Engineer
ML EngineerContributions:6 reviews, 11 commits, 42 PRs in 2 months
Contributions summary:William primarily contributed to the maintenance and expansion of the ivy library, a project focused on converting machine-learning code between frameworks. Their work included reformatting and refactoring code, adding functionality for linear algebra operations such as svd and eigvalsh, and implementing frontend functionalities for different machine-learning frameworks like JAX and Torch. This work directly supports the core functionality of the library.
machine-learningpythontensorflowpytorchnumpy
WilliamHirst/ivyWH
Sep 2022 - Dec 2022
The Unified Machine Learning Framework
Contributions:84 pushes, 15 branches in 3 months
pythondata-sciencedeep-learningmachine-learningframework-learning
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