Sudeep Agarwal - Vice President Of Product Management at Tubi

Sudeep Agarwal

Vice President Of Product Management at Tubi

San Francisco, California, United States

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Summary

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Rockstar

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Top School

Sudeep Agarwal is a product leader and hands-on builder with 11 years of experience shaping growth and product strategy, currently serving as Vice President of Product Management at Tubi in San Francisco. He combines enterprise and consulting roots (Oracle, McKinsey, Google) with startup-style execution, scaling user growth and monetization across streaming products. Technically fluent, he contributes code to open-source ML projects—adding front-end Chrome-extension UI and REST/Python modules for in-browser and deployed LLM inference in notable repos like mlc-ai/web-llm and mlc-ai/mlc-llm. That mix of product leadership and full-stack development lets him move quickly from customer insights to deployable ML features. He holds a BE (Hons.) from BITS Pilani and an MISM from Carnegie Mellon, reflecting a strong foundation in both engineering and management. Colleagues describe him as a pragmatic strategist who still enjoys shipping code that directly impacts users.

11 years of coding experience

14 years of employment as a software developer

BITS Pilani, Birla Institute of Technology and Science

Kendriya Vidyalaya Sangathan

MISM, MISM at Carnegie Mellon University

English, Hindi

Stackoverflow

Stats

796reputation

33kreached

20answers

9questions

Github Skills (23)

javascript10

language-model10

python10

typescript10

chrome-extension10

llm10

huggingface10

typescript-types10

rest-api10

typescripts10

tvm9

react9

html8

css8

webgpu8

Programming languages (7)

TypeScriptJavaScriptHTMLSwiftJupyter NotebookRubyPython

Github contributions (5)

mlc-ai/mlc-llm

May 2023 - Oct 2023

Universal LLM Deployment Engine with ML Compilation

Role in this project:

Full-stack Developer

Contributions:26 reviews, 19 PRs, 1 push in 5 months

Contributions summary:Sudeep implemented significant features related to model loading, configuration, and deployment within the MLC-LLM framework. Their work included adding support for custom model paths, downloading weights from Hugging Face, and integrating various model configurations (Llama, GPT-NeoX, Moss). Furthermore, the user contributed to the development of a Python chat module and a REST API, enhancing the framework's usability and deployment capabilities. They also refactored the REST API and added support for the Gorilla model.

language-modelllmmachine-learning-compilationtvm

mlc-ai/web-llm

Jun 2023 - Dec 2023

High-performance In-browser LLM Inference Engine

Role in this project:

Full-stack Developer

Contributions:1 review, 8 PRs, 7 comments in 5 months

Contributions summary:Sudeep primarily contributed to the front-end development of a Chrome extension for the `web-llm` project. They implemented the UI components for the extension, including the input field, submit button, loading indicators, and answer display. Additionally, the user integrated the `ChatRestModule` and `ChatModule` for interacting with both a local server and the WebGPU backend, facilitating user interaction with the model. They also added support for stuff QA using the context in the active tab.

chatgptdeep-learninglanguage-modelllmtvm

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