Develop on-device Runtime SW stack to deploy Machine Learning (ML) models on mobile devices for Google's Tensor SoCs, focusing on Camera, Speech, and Ambient Experiences on Pixel devices.
Requirements
- software development in one or more programming languages
- working with embedded operating systems
- hardware and ML accelerators (e.g., experience at a company that builds ML chips)
- machine learning algorithms and computer architecture
- on-device ML (e.g., an understanding of NLP, image and vision, on-device GenAI)
Responsibilities
- Develop on-device Runtime SW stack to deploy Machine Learning (ML) models on mobile devices.
- Track and drive performance and power optimizations to enable large on-device models.
- Support customers with quickly deploying their ML models to the Tensor TPU.
- Work with application software teams to prototype and enable new use cases on Tensor SoCs.
- Participating in, or leading technical design reviews with peers and stakeholders.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency)
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on SW, Hardware (HW) and quality.
Other
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting.
- 2 years of experience working with embedded operating systems.
- manage project priorities, deadlines and deliverables.
- display leadership qualities and be enthusiastic to take on new problems across the full-stack
