Denali Molitor
Software Engineer at Google
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolDenali Molitor is a software engineer and PhD-trained applied mathematician based in Seattle with nine years of experience bridging research and production machine learning systems. Currently at Google, she brings deep technical rigor from her UCLA PhD and hands-on ML contributions to flagship open-source projects like TensorFlow and NLTK, where she improved core n-gram generation and gradient analysis test coverage. Her background as a research intern and extensive academic research informs a methodical approach to model correctness, performance optimizations, and numerical analysis. Colleagues rely on her for careful attention to edge cases—evidenced by fixes to padding, einsum depth handling, and HLO value semantics—and for translating provable math into reliable code.
9 years of coding experience
Bachelor of Arts (B.A.), Mathematics, Bachelor of Arts (B.A.), Mathematics at Colorado CollegeUniversity of California, Los Angeles
Stackoverflow
36reputation
2kreached
2answers
0questions
Github Skills (18)
operation10
python10
nltk10
machine-learning10
deep-learning10
tensorflow10
deep-neural-networks10
natural-language-processing10
hla10
neural-network10
iterator10
nlp10
testing9
backpropagation9
linear-algebra9
Programming languages (5)
Github contributions (5)
nltk/nltk
Jun 2020 - Jul 2020
NLTK Source
Role in this project:
Data Scientist
Data ScientistContributions:23 commits, 1 PR, 21 comments in 29 days
Contributions summary:Denali primarily contributed to the NLTK (Natural Language Toolkit) repository by modifying and improving the `everygrams` function, a core component for generating ngrams from text sequences. Their work involved accommodating iterable inputs, fixing padding issues, and optimizing the function's performance. Furthermore, the user corrected a docstring typo and updated test outputs to reflect the changes made to the `everygrams` function, demonstrating attention to detail and a focus on improving the library's functionality.
nlppythonmachine-learningnltknatural-language-processing
tensorflow/tensorflow
Jun 2021 - Jun 2022
An Open Source Machine Learning Framework for Everyone
Role in this project:ML Engineer
ML EngineerContributions:11 commits in 11 months
Contributions summary:Denali contributed to the `tensorflow/tensorflow` repository, which focuses on machine learning. Their work included adding tests for `WeightGradient`s and `ActivationGradient`s, suggesting a focus on model training and backpropagation. The commits also involved handling while loops in einsum depth analysis and fixing conditional handling within the context of HLO value semantics analysis, which is crucial for the correct execution and optimization of machine learning models. They also added an option to select only the op name from metadata when printing an HLO instruction.
pythondata-sciencedeep-learningmlmachine-learning
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