Minimum qualifications:- 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.
- 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience developing accessible technologies.
About the jobWe are seeking a motivated and experienced software engineer to be a key contributor in building and owning our cutting-edge, cross-device test infrastructure. In this role, you will play a crucial part in transforming our software development lifecycle, empowering our test engineers and developers to achieve faster release cycles and higher quality software. You will leverage your deep technical skills to construct robust, scalable test systems and explore and implement AI-powered automation to drive efficiency and innovation.
The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $211000 (USD) 15% bonus target bonus equity benefits
Learn more about benefits at Google .
Responsibilities - Write product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (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.
- Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
