Benjamin Kitor is a Machine Learning Engineer with eight years of hands-on experience at the intersection of HPC, networking, and distributed deep learning, currently finishing a MASc at Queen’s University and working at TensorWave. He built and optimized MPI collective algorithms using UCX to accelerate distributed DL benchmarks and has production networking experience from a senior role at GigaIO. Comfortable across CUDA, MPI, and systems-level software, he’s also contributed to open-source projects like the popular spotify-tui, adding shuffle/playback features in Rust. Described as both a fast learner and coachable leader, he blends research rigor with practical engineering to improve performance-critical systems. Based in the United States, he seeks teams tackling world-changing technical challenges where low-level optimization meets ML at scale.
8 years of coding experience
3 years of employment as a software developer
Master of Applied Science Computer Engineering, Master of Applied Science Computer Engineering at Queen's University
Contributions:11 commits, 1 PR, 7 comments in 3 days
Contributions summary:Benjamin primarily focused on enhancing the "spotify-tui" application's functionality related to random song playback. They implemented features to allow playing random songs from playlists, saved tracks, and the "MadeForYou" context. The commits involved modifications to `src/handlers/track_table.rs`, adding new methods for shuffling and initiating playback based on different contexts within the application. They also contributed to the UI's help documentation.
Contributions:95 pushes, 3 branches in 2 years 4 months
mpi
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Benjamin Kitor - Machine Learning Engineer at TensorWave