Strong systems foundations / growing toward AI research
I build dependable software and distributed systems. Now I’m applying that rigor to machine learning—studying the foundations, shipping AI-enabled tools, and moving deliberately toward frontier work.
Proven engineering work across infrastructure, collaboration, performance, and emerging AI tooling—built around measurable outcomes rather than claims.
Strong systems engineering is the base. Machine learning is the next layer—approached through study, implementation, and honest iteration.
Operating principle
Make the complex legible. Make the critical reliable. Remove everything else.
Understand
Implement
Measure
Worked on AI-powered developer productivity and automated testing platforms, leading frontend development and modernizing the core engineering dashboard.
Notes on systems, machine learning, and the discipline of learning difficult things—written to clarify, not to perform.
Peer-reviewed / IEEE Xplore
IEEE · 2022
This paper proposes a machine learning algorithm that basically utilizes a specific type of Recurrent Neural Net (RNN) known as Long Short Term Memory (LSTM), where the weights and biases are adjusted as per the singleton data points using SGD
I’m interested in roles and collaborations where strong engineering, product judgment, and machine learning meet. If that sounds like your team, I’d like to hear about it.
Designed and built with care.
© 2026 Prateek Bhatt