Machine Learning Architect, Audio

Key Skills

Java Programming, Python Programming, SQL, Machine learning techniques, TensorFlow, Algorithms

Job Description

Minimum qualifications:

• Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, a similar field or equivalent practical experience.
• 7 years of experience in semiconductors and/or consumer electronics.
• Experience working cross-functionally.

Preferred qualifications:

• Master's degree or PhD with emphasis in Machine Learning Applications.
• 10 years of relevant industry experience.
• End-to-end development experience (concept to product) as a key technical contributor.
• Experience on deploying ML algorithms on resource constrained hardware.
• Direct experience in implementing and optimizing ML workloads.
• Knowledge of ML tool-chains and run-time flows.

About the job

The audio architecture team works to deliver the highest quality and lowest power audio solutions that power Google's mobile products. As a member of the Pixel Audio Architecture team, you will be defining the next generation of innovative audio use cases to create radically helpful experiences for our users.

As a Machine Learning (ML) architect, you will be working with advanced AI research teams and ML deployment teams to define the next generations of ML use cases in our products. You will work cross-functionally to define compute, memory, and power requirements for these ML use cases to help guide the hardware and software implementation decisions for future generations of devices. Once defined, you will follow through to ensure proper implementation of these use cases to ensure our users have the most innovative and delightful experiences.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

Responsibilities

• Work closely with research ML teams and audio ML teams to understand feature networks and the TFL/TFLm implementations on target hardware.
• Generate ML use cases and feature budgets for memory and MIPS to help the product team understand implementation requirements.
• Work closely with algorithm and software deployment teams to ensure proper optimization in order to meet budgets and product KPIs.
• Be familiar with TensorFlow Framework and specifically knowledgeable about TFL and TFLm runtime workflows.
• Understand audio/ambient experience roadmaps and ML features/algorithms that drive those experiences.