Christy Bergman
Staff Developer Advocate
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolChristy Bergman is a Staff Developer Advocate in San Francisco with 11 years building AI infrastructure, GenAI, and developer experiences across startups and cloud giants. She blends hands-on ML engineering and documentation chops—contributing tutorials and RLlib docs to Ray and practical RecSim recommendation-system tutorials for Anyscale—with deep operational knowledge from roles at AWS and Anyscale. A frequent speaker and educator, she has built demos, blogs, and community programs that translate vector databases, LLMs, RAG, and agent patterns into usable developer workflows. Christy also runs a local nonprofit for remote tech workers and freelanced as a GenAI consultant, showing a knack for combining community building with applied AI. Her background in operations research (Stanford) and long track record across production analytics, distributed systems, and forecasting gives her a rare mix of rigorous modeling and developer-focused product thinking.
11 years of coding experience
22 years of employment as a software developer
Certificate French language & civilisation superior level, Certificate French language & civilisation superior level at Université Paris-SorbonneMaster of Science (M.S.) Operations Research, Master of Science (M.S.) Operations Research at Stanford University
English, French
Stackoverflow
46reputation
3kreached
5answers
0questions
Github Skills (20)
python10
machine-learning10
reinforcement-learning10
time-series-forecasting10
jupyter-notebook10
ray10
documentation10
data-analysis10
data-visualizations9
data-visualisation9
data-visualization9
pytorch8
data-science8
tensorflow7
modin6
Programming languages (5)
Github contributions (5)
aws-samples/amazon-forecast-samples
Nov 2020 - Jul 2021
Notebooks and examples on how to onboard and use various features of Amazon Forecast.
Role in this project:
Data Scientist
Data ScientistContributions:1 review, 182 commits, 102 PRs in 7 months
Contributions summary:Christy primarily contributes to the development and documentation of a Jupyter Notebook that focuses on item-level accuracy metrics within the context of an Amazon Forecast project. The user refactors and updates the notebook by correcting code errors, fixing markup and fixing the image path, and enhancing the overall presentation, including visualizations and explanations. The code changes involve custom metric calculations and demonstrations, reflecting an effort to analyze and improve model performance.
amazon-forecastonboardpythondata-scienceamazon
anyscale/academy
Sep 2022 - Oct 2022
Ray tutorials from Anyscale
Role in this project:ML Engineer
ML EngineerContributions:58 commits, 55 PRs, 46 pushes in 1 month
Contributions summary:Christy added a tutorial for a recommendation system using RecSim, a reinforcement learning environment. The code changes involve setting up the RecSim environment, including defining parameters like the number of candidates and slate size. This work likely involves modifying existing code or integrating new code to facilitate the creation and evaluation of the RL environment for recommendation systems.
raypythonmachine-learning
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