Roy Hvaara
Software Engineer at Arundo Analytics, Inc.
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolRoy Hvaara is a seasoned software engineer with about a decade of experience delivering reliable systems and ML-focused software, based in San Francisco. He previously contributed to Google as a Site Reliability Engineer, helping scale and stabilize critical infrastructure through several roles from 2020 to 2024. In open source, he has contributed to PyTorch and Hugging Face Transformers, refining Metal Performance Shaders support, improving tensor operations, and updating TF/JAX integrations. His career also spans Arundo Analytics as a Senior Software Developer and earlier roles at KickBack and VG Verdens Gang, showcasing a strong blend of software engineering and systems administration. With a Bachelor’s degree in Informatics: Programming and Networks from the University of Oslo, he combines production-grade software craftsmanship with a practical ML research sensibility. He is community-minded and eager to connect with peers to share knowledge and build impactful ML and reliability tooling.
10 years of coding experience
9 years of employment as a software developer
University of OsloCourseraPhysics, Biology, Math and Chemistry, Physics, Biology, Math and Chemistry at Re videregåendeMedicine, Medicine at University of Pécs
English, Norwegian
Stackoverflow
139reputation
4kreached
5answers
0questions
Github Skills (29)
pytorch10
python10
metal-performance-shaders10
machine-learning10
metalperformanceshaders10
tensorflow210
deep-learning10
tensorflow10
gpu10
neural-network10
tensor10
jax10
mps10
numpy9
flax9
Programming languages (9)
Github contributions (5)
pytorch/pytorch
Apr 2024 - Feb 2025
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Role in this project:
ML Engineer
ML EngineerContributions:23 reviews, 19 PRs, 228 comments in 10 months
Contributions summary:Roy primarily contributed to improving the PyTorch framework's support for Metal Performance Shaders (MPS), focusing on optimizations, bug fixes, and new feature implementations related to tensor operations and neural network modules. They addressed issues with boolean data types, batch normalization with sliced inputs, and the `fftfreq` function. Furthermore, the user added and updated regression tests to ensure the correctness of MPS implementations, especially regarding `nn.Conv3d` and `F.linear`. Their work also involved refining error messages and adding autocast support.
pythongpu-accelerationdeep-learninggpunumpy
huggingface/transformers
Jan 2023 - Jan 2023
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Role in this project:ML Engineer
ML EngineerContributions:1 review, 1 commit, 9 PRs in 1 day
Contributions summary:Roy primarily contributed to the Hugging Face Transformers library, making various improvements related to the TensorFlow and JAX integrations. Their work included refactoring code to remove deprecated NumPy type aliases, adding support for TensorFlow's `is_symbolic_tensor` predicate, and replacing instances of `jnp.array` with `jnp.ndarray` in JAX code. They also updated dependencies to use the latest Keras initializers.
pythonbertspeech-recognitionstate-of-the-artflax
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