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Staff Software Engineer, On-Device Machine Learning

Google
Sunnyvale, USA
Senior · 8+ years experience
Onsite
USD 207000-300000 / year
Discovered 1 weeks ago

Full Job Posting

Responsibilities

  • Enable one or more areas in Google AI Edge Developer Tools such as AI Edge Gallery (Gemma's showcase app for on-device Gemma 0-day), Developer Device Platform (Device farm with AI, enabling developers to test/eval/deploy apps and models across device), and AI Edge Eval (innovative eval framework for on-device model and harness).
  • Train task-specific models of in-app AI enabling Gemma model/runtime co-design (quantization, conversion), build industry-leading on-device AI solutions (voice translate, generative image editing)
  • Enable tooling of GTM for on-device Gemma 0-day (AI Edge Gallery), helping developers to test/eval/deploy across devices.
  • Enable on-device deployment of key models across various accelerators (GPU/Pixel TPU/NPUs/CPU) on Android, Chrome, and more.
  • Improve performance of on-device model inference via optimizations in the model presentation, on-device runtime and kernel implementation.

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience with software development in C++ programming language.
  • 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
  • 5 years of experience leading ML design and optimizing end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Preferred qualifications:

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • 8 years of experience with data structures and algorithms.
  • 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  • 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
  • Experience in deploying on-device Machine Learning models.

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