About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you develop the machine learning system and models that power the Pixel personal agent. This includes tasks such as data collection design, data engineering, feature engineering, model training, and model evaluation. You will work with engineers, researchers and product managers across Google to design and implement new features for the personal agent.
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

• Develop applications on Android/Pixel.
• Propose, design and implement data collection solutions.
• Design evaluation framework and carry out evaluations of the machine learning models.
• Stay informed on the latest machine learning techniques and technologies and apply them to our technical solutions.
• Collect and tune data to develop, maintain, and evaluate machine learning models.