Neema Mashayekhi
Senior Software Engineer, Machine Learning at ByteDance
San Francisco Bay Area United States
Summary
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Rockstar🎓
Top SchoolNeema Mashayekhi is a Senior Software Engineer specializing in machine learning with five years of industry experience and a strong foundation in data engineering and MLOps across AWS, Azure, Databricks, Kubernetes, and Docker. Based in the San Francisco Bay Area, she combines hands-on expertise in Python, R, Spark/PySpark, H2O, and scikit-learn with practical model management and deployment skills for production systems. Her background spans applied data science roles at Intel and H2O.ai and now ML engineering at ByteDance, reflecting a trajectory from domain-focused analytics to scalable ML platforms. She has contributed technical documentation to the well-known open-source H2O-3 project, improving clarity around models like Random Forest and XGBoost—an indicator of both deep tool familiarity and attention to developer experience. Trained as a chemical and biological engineer (PhD) and having led process engineering earlier in her career, she brings an experimental, measurement-driven mindset to ML model development and operationalization.
5 years of coding experience
17 years of employment as a software developer
Doctorate, Chemical and Biological Engineering, Doctorate, Chemical and Biological Engineering at Northwestern UniversityBachelor, Chemical and Biochemical Engineering, Bachelor, Chemical and Biochemical Engineering at University of California, Santa Barbara
Stackoverflow
932reputation
28kreached
65answers
0questions
Github Skills (13)
h2o10
restructuredtext10
documentation10
random-forest7
xgboost7
interaction6
gbm6
machine-learning6
automl6
python6
cross-validation6
r6
data-science5
Programming languages (6)
Github contributions (5)
h2oai/h2o-3
Jun 2020 - Jan 2022
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Role in this project:
Technical Writer
Technical WriterContributions:29 reviews, 13 commits, 11 PRs in 1 year 7 months
Contributions summary:Neema primarily contributed to the documentation of the H2O-3 project. Their work involved updating and correcting documentation files written in reStructuredText (.rst) format. The user fixed typos, clarified explanations, and updated code examples within the documentation, including areas like Random Forest models, explanation features, and XGBoost model parameters. This work helps improve the clarity, accuracy, and usability of the project's documentation.
xgboostgampythonk-meansautoencoders
neemah2o/conductor-h2o-sparklingwater
Feb 2021 - Jan 2022
An integration of H2O Sparkling Water as a notebook for IBM Spectrum Conductor.
Contributions:1 review, 4 PRs, 10 pushes in 11 months
h2oconductornotebookspectrumibm
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