Venkata Gorthy
Director, AI Search Platform
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolVenkata Gorthy is a product-focused engineering leader with 11 years of experience building and scaling AI, search, and data platforms for enterprise and consumer-scale products. Currently Director of AI Search Platform in the Bay Area, he specializes in 0→1 product creation, cross-functional alignment, and turning technical vision into roadmaps that drive measurable business and developer impact. He has led high-performing, cross-disciplinary teams across ML, data, backend and platform domains at companies including Moveworks, Anyscale, and Uber, where his teams powered large-scale search, ranking, and geolocation systems. At Anyscale he transformed Data, Training, and ML Observability into a flagship revenue-driving platform, and his open-source contributions to Ray improved Parquet and tensor handling for distributed ML workloads. Known for developing EMs and senior ICs while shaping org structure and culture, he combines deep engineering rigor with customer-focused product strategy.
11 years of coding experience
14 years of employment as a software developer
Masters, Computer Science, Masters, Computer Science at Arizona State UniversitySelf Driving Nano Degree Program, Term2, Self Driving Nano Degree Program, Term2 at UdacityBachelor of Engineering, Electronics and Communications, Bachelor of Engineering, Electronics and Communications at Osmania University
English, Telugu, Hindi
Github Skills (11)
parquet10
machine-learning10
ray10
pyarrow10
python10
data-engineering10
pandas9
distributed-systems8
data-science8
tensorflow8
optimization7
Programming languages (4)
Github contributions (5)
ray-project/ray
Jan 2023 - Jan 2023
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Role in this project:
ML Engineer & Data Engineer
ML Engineer & Data EngineerContributions:43 reviews, 2 commits, 6 PRs in 1 day
Contributions summary:Venkata primarily contributed to the Ray project's data and machine learning functionalities. They added support for partition columns in writing Parquet files, enhancing data storage and manipulation capabilities within the Ray ecosystem. Furthermore, the user addressed issues related to handling tensor types within the ParquetDatasink and fixed an expression evaluator to handle negative numbers. They also made optional the `num_blocks` argument in repartition.
pythonconsistsruntimetensorflowserving
gvspraveen/ray_playground
Dec 2022 - Mar 2024
Contributions:2 PRs, 51 pushes, 1 branch in 1 year 3 months
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