Ajay Borra
Software Engineering LMTS at Salesforce
Austin, Texas, United States
Summary
👤
Senior🎓
Top SchoolAjay Borra is a Lead Software Engineer based in Austin with 11 years of experience building AI-driven and cloud-native systems at Salesforce. He has led development of production AI services like ApexGuru that detect code anti-patterns and improve performance, and has a consistent record of inventing patents in machine learning and infrastructure. Ajay bridges research and production—contributing to open-source AutoML tooling like TransmogrifAI by refactoring core workflows and adding robust test coverage for data IO. His background spans designing AIOps automation, time-series detection, and scalable microservices, grounded in an MS in Computer Science from Georgia Tech. Known for reducing operational fatigue through automation, he combines pragmatic engineering with a knack for turning ML research into deployable, high-impact services.
11 years of coding experience
10 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Georgia Institute of TechnologyBachelor of Technology (B.Tech.) Computer Science, Bachelor of Technology (B.Tech.) Computer Science at GITAM Deemed University
English, Telugu, Hindi
Github Skills (9)
scala10
apache-spark10
automated-machine-learning10
testing10
data-pipelines9
data-pipeline9
csv9
avro9
machine-learning8
Programming languages (5)
Github contributions (5)
salesforce/TransmogrifAI
Aug 2018 - Nov 2018
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning
Role in this project:
Back-end Developer
Back-end DeveloperContributions:14 commits, 9 PRs, 27 comments in 3 months
Contributions summary:Ajay primarily focused on refactoring and improving the core functionality of the TransmogrifAI library. Their contributions involved updating project names, modifying core components related to workflow execution and stage management. In addition to this, the user added comprehensive test coverage for various utility classes like CSV and Avro Input/Output, which involved the creation of new unit tests for data reading, conversion, and processing.
pythonsalesforcetransformationstransmogrifyestimators
ajayborra/TransmogrifAI
Aug 2018 - Feb 2025
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Spark with minimal hand tuning
Contributions:232 pushes, 62 branches in 6 years 7 months
pythondata-sciencemachine-learningmlopsspark
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