Nicholas Farn
Research Engineer at Luma
California, United States
Summary
👤
Senior🎓
Top SchoolNicholas Farn is an ML Engineer with a decade of experience building large-scale NLP and ML systems, currently at Apple after several applied-science roles in Microsoft's AI division. He specializes in large language models, neural hallucination mitigation, and productionizing document and query classification pipelines. His work balances research rigor and engineering pragmatism—contributing to open-source probabilistic tooling like pomegranate early in his career and implementing practical HMM and Bayesian examples. Trained at UCLA (MS) and University of Washington (BS), he combines strong probabilistic foundations with hands-on systems experience, often surfacing subtle data- and model-driven failure modes before they reach users.
10 years of coding experience
9 years of employment as a software developer
Bachelor of Science (B.S.) Applied and Computational Math Sciences, Bachelor of Science (B.S.) Applied and Computational Math Sciences at University of WashingtonUniversity of California, Los Angeles
English, Chinese
Github Skills (5)
bayesian-network10
probabilistic-graphical-models10
machine-learning10
python10
pytorch8
Programming languages (5)
Github contributions (5)
jmschrei/pomegranate
Jan 2016 - Jun 2016
Fast, flexible and easy to use probabilistic modelling in Python.
Role in this project:
Data Scientist
Data ScientistContributions:22 commits, 21 PRs, 6 comments in 5 months
Contributions summary:Nicholas implemented and documented a Hidden Markov Model (HMM) for a rainy-sunny scenario, showcasing the use of `pomegranate` for probabilistic modeling. They added code for generating and checking the probability of sequences using the HMM. They extended this by adding multiple examples using Bayesian Networks, providing code for various use cases such as tied states and a coin toss example. These examples highlight the user's skill in using the library and applying it to various classification tasks.
pythonmachine-learningprobabilistic-graphical-modelspytorch
neonrights/swinemeeper
May 2018 - Sep 2018
Contributions:56 commits, 52 pushes, 1 branch in 4 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.