Software Engineer III, Mobile, Android, Applied AI
Summary
Android engineer on Google's Automotive AI Agent team, building the on-device SDK and reference apps for an AI assistant running on Android Automotive OS. Day to day: writing and reviewing Java/Kotlin code, integrating on-device AI/LLM features, debugging system issues, and testing across complex system integrations.
Android is Google’s mobile operating system powering more than 3 billion devices worldwide. Android is about bringing computing to everyone in the world. We believe computing is a super power for good, enabling access to information, economic opportunity, productivity, connectivity between friends and family and more. We think everyone in the world should have access to the best computing has to offer. We provide the platform for original equipment manufacturers (OEMs) and developers to build compelling computing devices (smartphones, tablets, TVs, wearables, etc) that run the best apps/services for everyone in the world.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
- Write product or system development code.
- Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience programming in Java or Kotlin.
- 2 years of experience with Android application development.
- Experience building and maintaining distributed systems, cloud APIs, and mobile/embedded SDKs (Android).
- Experience with AI/ML technologies, particularly Large Language Models (LLMs) or Natural Language Understanding (NLU).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 2 years of experience with performance, systems data analysis, visualization tools, or debugging.
- 2 years of experience with data structures and algorithms in either an academic or industry setting.
- Experience developing accessible technologies.
- Experience in code and system health, diagnosis and resolution, and software test engineering.