Rahul Palamuttam
Software Engineer at Waymo
United States
Summary
🤩
Rockstar🎓
Top SchoolRahul Palamuttam is a seasoned software engineer with 11 years of experience specializing in ML compilers and high-performance data runtimes, currently building ML compiler infrastructure at Waymo. His background spans research-grade systems at Stanford (contributing to the Weld intermediate language and runtime) to production-focused compiler work at DeepMind, reflecting a blend of deep systems thinking and applied ML engineering. He has a strong track record in backend and data-infrastructure projects—adding language features, LLVM codegen, and sorting/group-merger logic in Weld, and integrating Kafka sinks for Spark-based web crawlers. Rahul’s hands-on experience with Ray, Apache Arrow, Spark, and LLVM shows he bridges research prototypes to scalable deployments, and his multi-institution education (UC Santa Cruz, UC San Diego, Stanford) complements a long history of internships at places like JPL and GE Digital. Notably, he pairs low-level compiler changes (char type, slice operator) with practical streaming and distributed systems work, making him effective at optimizing end-to-end ML data paths.
11 years of coding experience
7 years of employment as a software developer
High school diploma, High school diploma at Bellarmine College Preparatory High SchoolUniversity of California, San DiegoUniversity of California Santa CruzMaster's degree, Computer Science, Master's degree, Computer Science at Stanford University
Stackoverflow
21reputation
1kreached
4answers
0questions
Github Skills (27)
spark10
llvm10
kafka10
data-analytics10
scala10
code-generation10
rust10
data-structure9
performance-monitor9
algorithm9
algorithms9
distributed-systems9
big-data9
performance-analysis9
data-structures9
Programming languages (6)
Github contributions (5)
weld-project/weld
Feb 2017 - Apr 2019
High-performance runtime for data analytics applications
Role in this project:
Backend Developer
Backend DeveloperContributions:26 commits, 9 PRs, 2 pushes in 2 years 3 months
Contributions summary:Rahul primarily contributed to the Weld project by implementing new functionalities related to data types and functions within the Weld language. This included implementing the char type, modifying tokenization, parsing, and LLVM code generation to support it. Furthermore, the user added a length function and a slice operator, enhancing the capabilities of the Weld language. They also implemented a basic sorting function and made changes to the groupmerger.
data-analyticsstanforddataanalyticsmachine-learning
USCDataScience/sparkler
Aug 2016 - Sep 2016
Spark-Crawler: Apache Nutch-like crawler that runs on Apache Spark.
Role in this project:Back-end Developer
Back-end DeveloperContributions:5 commits, 4 PRs, 5 comments in 1 month
Contributions summary:Rahul primarily focused on extending the Apache Spark-based crawler's capabilities. They implemented a Kafka connector data sink to enable streaming crawl data to Kafka. The user also added configurations related to Kafka, including listeners and topics and enabled/disabled the Kafka. They also modified the crawler to output status codes.
apache-sparkcrawlernutchsparksolr
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