Summary
Eli Lucherini is a Senior Machine Learning Engineer in San Francisco with nine years of experience building MLOps and real-time ML systems at scale. He has moved between research and product roles—from implementing memory allocators and distributed algorithms in embedded and systems settings to training RNNs and shipping production feature pipelines for precision health clients like Walmart. At Apple and IBM he focused on privacy-preserving and time-series ML work, while at HEALTH[at]SCALE he led end-to-end feature engineering, model development, and CI/CD automation. Now at Conviva he continues to operationalize real-time models, combining a PhD-level systems background from Princeton with hands-on software engineering across C++, Python, and cloud MLOps. Notably, his career blends low-level performance wins (reducing cache misses on ARM64) with production ML reliability for large-scale user and healthcare applications.
9 years of coding experience
5 years of employment as a software developer
Bachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at Università di Pisa
Master's degree Embedded Computing Systems, Master's degree Embedded Computing Systems at Scuola Superiore Sant'Anna
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Princeton University
German, English, Italian