Annika Brundyn
Applied AI at OpenAI
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAnnika Brundyn is an Applied AI practitioner with seven years of experience building ML systems and advising on GenAI solutions across research and industry. Currently at OpenAI after leading GenAI specialization as a Senior Solutions Architect at NVIDIA, she blends hands-on model development with product-facing architecture and deployment. Her background spans production ML for social impact and education—ranking services for Ofsted and modeling student success for an 80k-user platform—alongside commercial work optimizing personalized offers for major banks. An active contributor to pytorch_lightning_bolts, she implemented VAE, linear and logistic regression templates and datamodules, reflecting a strong foundation in probabilistic modeling and tooling for researchers. Trained in data science at NYU with actuarial and statistics roots from the University of Cape Town, she brings rigorous quantitative skills paired with practical engineering and stakeholder-facing communication. Notably, she also represented South Africa on STEM inclusion policy at the G(irls)20 summit, signaling a commitment to broadening access to technical fields.
8 years of coding experience
5 years of employment as a software developer
BSc Honours in Statistics Statistics, BSc Honours in Statistics Statistics at University of Cape TownMaster's degree Data Science, Master's degree Data Science at New York UniversityIARU Global Summer Program Multi-/Interdisciplinary Studies General, IARU Global Summer Program Multi-/Interdisciplinary Studies General at University of Cambridge
English, Afrikaans, Spanish, French
Github Skills (14)
variational-autoencoder10
pytorch10
machine-learning10
logistic-regression10
pytorch-lightning10
python10
autoencoder10
linear-regression10
ai9
deep-learning9
image-processing6
cgan6
dcgan6
natural-language-processing5
Programming languages (3)
Github contributions (5)
Lightning-Universe/lightning-bolts
Apr 2020 - Nov 2020
Toolbox of models, callbacks, and datasets for AI/ML researchers.
Role in this project:
ML Engineer
ML EngineerContributions:9 reviews, 13 commits, 13 PRs in 7 months
Contributions summary:Annika's primary contribution involves the development of a Variational Autoencoder (VAE) model, including the implementation of encoder and decoder components within the `pytorch_lightning_bolts` framework. Their work encompassed the creation of a basic VAE template, the addition of argument parsing capabilities, and iterative refinements to the model's architecture, such as changing encoder dimensions. Further contributions include implementing a Linear Regression model and a Logistic Regression model, including datamodules. Their changes also involve integration and testing.
aicallbackmachine-learningpytorchimage-processing
annikabrundyn/da_vinci
Oct 2020 - May 2021
Contributions:39 reviews, 567 commits, 48 PRs in 6 months
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