Julie Tibshirani
Hello, world! I’m a software engineer focused on developer infrastructure and search. I work on the developer platform team at Databricks and serve as an Apache Lucene committer and PMC member.
I love building software that’s empowering and joyful to use. I’m an open source enthusiast, and shared my experience joining the open source search community in Finding a home (and career) in the open source community.
Before Databricks, I worked at Elastic on the Elasticsearch search engine, as well as Sourcegraph and Palantir Technologies. I hold an M.S. in Computer Science and B.S. in Math from Stanford University.
Selected work
🔎 Code search
Sourcegraph is a widely used code intelligence platform that helps enterprises work efficiently with large, complex codebases. I helped introduce Sourcegraph’s semantic code search capability, allowing users (and LLMs!) to ask questions about large codebases in natural language.
- Beyond working set memory: understanding the cAdvisor memory metrics (Sourcegraph blog, 2025)
- Keeping it boring (and relevant) with BM25F (Sourcegraph blog, 2025)
🔢 Vector search
Thanks to a new generation of machine learning models that can powerfully represent text as vectors, there’s been a surge of interest in vector-based semantic search. I led Elastic’s effort to introduce vector search in Lucene and Elasticsearch, helping extend these systems to become powerful “vector databases”.
- Introducing approximate nearest neighbor search in Elasticsearch (Elastic blog, 2022)
- Implementing academic papers: lessons learned from Elasticsearch and Lucene (Elastic blog, 2021)
🌲 Machine learning for causal inference
Causal inference allows for determining the effect of an action on a larger system. The generalized random forests (grf) method combines insights from statistics and machine learning to enable causal analysis. I authored the grf software package, which won an inaugural Stanford Open Source Software prize for its research impact, quality, and dedication to open source principles.
- Generalized Random Forests (Annals of Statistics, 2019)
- Local Linear Forests (Journal of Computational and Graphical Statistics, 2020)
Other
⛰️ Backcountry cooking recipes. I’m an avid backpacker and enjoy finding creative ways to eat well outdoors.
🤓 Unicode. I’m the proud sponsor of Unicode characters μ and σ.
