Keltin Grimes is an Associate Machine Learning Research Scientist at Carnegie Mellon University's Software Engineering Institute with eight years of experience building applied ML systems focused on robustness, security, and scalability. A CMU alum in Statistics & Machine Learning and Computer Science, he has moved from research assistantships on materials discovery to production-focused internships at Amazon and work on adversarial ML for cybersecurity. Keltin designs and deploys models and tooling—ranging from distributed hyperparameter optimization in PyTorch/TensorFlow to serverless APIs and active learning systems—bridging research and engineering. He combines rigorous academic training with practical impact inside institutional research settings, often translating novel Bayesian and active learning ideas into working prototypes. Outside work he’s an endurance athlete and competitive chess player, a mix that mirrors his discipline for long-term experiments and strategic problem solving.
8 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Statistics and Machine Learning, Computer Science, Bachelor's degree, Statistics and Machine Learning, Computer Science at Carnegie Mellon University
Contributions:19 commits, 13 PRs, 15 pushes in 1 day
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Keltin Grimes - Associate Machine Learning Research Scientist