Jay Franck is a Machine Learning Engineer with 9 years of experience deploying ML models into real-time production systems at scale, most recently improving PlayStation-facing systems and now building search relevancy and retrieval at Dropbox. He specializes in productionizing ranking and RAG systems—designing LambdaMART and TensorFlow Ranking models, optimizing endpoint latency, and expanding recall through query augmentation and vector-based retrieval. Jay pairs a deep research foundation (PhD in Astrophysics) with pragmatic engineering: he has migrated ETL pipelines to BigQuery/PySpark, tuned Solr boosts, and created realistic evaluation frameworks for LLM-integrated products. Known for squeezing both latency and accuracy gains, he blends model-level innovation with operational improvements like autoscaling and feature pruning to serve millions of users.
9 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Astrophysics, Doctor of Philosophy (Ph.D.) Astrophysics at Case Western Reserve University
M.S. Astrophysics, M.S. Astrophysics at San Diego State University
B.S. Astrophysics, B.S. Astrophysics at Michigan State University
Contributions:1 review, 9 PRs, 15 pushes in 4 years 5 months
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