Gayathri Murali
Director, GenAI at Meta
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolGayathri Murali is a Director of GenAI Partner Engineering at Meta with 12 years of experience building agentic AI platforms, personalization systems, and secure developer ecosystems. She led Meta’s end-to-end enterprise adoption of Llama—driving prompt optimization, fine-tuning, and distillation—and translates real-world usage into model and product roadmaps. Known for 0→1 platform building, she moves ambiguous problem spaces into scalable products that drive adoption, ecosystem growth, and monetization. Her background includes retail, eCommerce, and ad product engineering, and she contributes to open-source ML tooling—having improved PySpark ML persistence and model export/import for Apache Spark. Based in San Jose, she pairs hands-on engineering with strategic partner and evaluation frameworks to improve tool-calling accuracy and multi-step task completion.
11 years of coding experience
17 years of employment as a software developer
Master of Science (MSc) Integrated, Software Engineering, Master of Science (MSc) Integrated, Software Engineering at PSG College of Technology
English
Github Skills (11)
mle10
big-data10
machine-learning10
decision-tree10
pyspark10
spark10
python10
ml10
logistic-regression9
scala8
r7
Programming languages (2)
Github contributions (5)
apache/spark
Sep 2015 - Sep 2016
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
ML Engineer
ML EngineerContributions:27 PRs, 135 comments in 1 year
Contributions summary:Gayathri made significant contributions to the PySpark ML library, specifically focusing on adding export/import functionalities for various classification and regression models within the `pyspark.ml` module. Their work included implementing persistence (saving and loading) for Decision Tree models, Logistic Regression, and other machine learning algorithms. They also updated documentation, examples, and user guides to reflect the changes in SparkR related to machine learning APIs.
analyticspythondata-processingsqlapache
GayathriMurali/spark
Sep 2015 - Aug 2016
Contributions:82 pushes, 24 branches in 11 months
apachebig-datasparkscalaapache-spark
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