David Pitt is a machine learning scientist in New York with seven years of hands-on R&D experience building robotics and AI systems that accelerate real-world operations. Currently at Ultra, he focuses on applied research for robotic platforms and previously spent two years at Caltech’s AI4Science Lab where he maintained NeuralOperator, a leading open-source library for operator learning. He blends production ML engineering—shipping privacy-aware language features and calibration systems—with research contributions in memory-efficient, physics-informed neural operators. As founder of a consulting shop he delivered prototypes from lightweight RAG systems for 1k+ page documents to robotic manipulation demos, showing a knack for turning complex research into practical demos. A Harvey Mudd alum with honors in math and CS, he pairs rigorous theoretical training with a pragmatic, open-source-first approach to solving high-dimensional scientific and robotics problems.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Mathematics and Computer Science, High distinction, departmental honors in math, Bachelor of Science - BS, Mathematics and Computer Science, High distinction, departmental honors in math at Harvey Mudd College
Contributions:141 pushes, 1 branch in 1 year 8 months
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