Dan Melamed
Staff Software Engineer (Machine Learning) at LinkedIn
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolDan Melamed is a software engineer and machine learning leader with over a decade of experience building web-scale ML systems, LLM-driven products, and AI orchestration at Meta and LinkedIn. He has led cross-cutting initiatives—from a company-wide ontology migration affecting thousands of repos to embedding-based ranking and query understanding for fast-growing products—combining hands-on modeling with production-grade engineering. His background spans academia and industry research (including a PhD and work at Microsoft Research and AT&T Labs), and he has deep expertise in online learning, contextual bandits, and reinforcement-style systems. An active contributor to Vowpal Wabbit, he has fixed numerically tricky core algorithms and improved deterministic performance, reflecting his attention to mathematical correctness and reproducible systems. He mentors engineering teams, drives infra-level transformations, and still collects geek trophies—like a $16 bug-bounty check from Bjarne Stroustrup for finding errors in The C++ Programming Language.
10 years of coding experience
19 years of employment as a software developer
Bachelor of Science (BSc), Cognitive Science and Artificial Intelligence, Bachelor of Science (BSc), Cognitive Science and Artificial Intelligence at University of TorontoDoctor of Philosophy (PhD), Computer and Information Science, Doctor of Philosophy (PhD), Computer and Information Science at University of Pennsylvania
English, Russian, French
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (21)
c-language10
numerical10
mathematics10
machine-learning10
mathics10
math10
maths10
numerics10
numerical-methods10
stability10
cpp10
cprogramming-language10
numeric10
elearning9
active-learning8
Programming languages (3)
Github contributions (5)
VowpalWabbit/vowpal_wabbit
Oct 2015 - Aug 2016
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:90 commits, 11 PRs, 19 comments in 10 months
Contributions summary:Dan primarily focused on fixing issues related to exponential functions and numerical stability within the core Vowpal Wabbit codebase. Their work included addressing a bug causing incorrect results with `exp(-inf)` on Windows and implementing a `correctedExp` function. Additionally, the user was involved in refactoring and improving code related to the loss functions, LDA core, and boosting, contributing to improved mathematical accuracy. They also introduced changes for improved performance in specific data structures, with deterministic output.
hashingtechniquescpppythonactive-learning
danmelamed/vowpal_wabbit
Oct 2015 - Aug 2016
Contributions:63 pushes, 11 branches in 9 months
hashingtechniquespythonwabbitreductions
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