Collaborate with multiple ML teams across vision, LLM and speech to architect ML application code that reduces technical debt and time to delivery. Develop and maintain data utilities for various text, image, speech data and ensure flexibility to new data. Automate verification and testing of ML models on RDU. Architect, develop and maintain evaluation benchmark infrastructure for ML models across modalities. Coordinate ML release process with compiler, runtime and other complementary software team releases to ensure smooth production delivery. Set software standards (testing, code structure, gotchas, error handling, oncall) for ML teams working with complementary software teams; lead by example and codify these into code and documentation.

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