US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Write and test product or system development code.
Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
Review code developed by other developers 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.
Minimum qualifications
Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
Experience in Generative AI (Large Language Models, Multi-Modal, Large Vision Models).
Experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, natural language processing, or other ML disciplines.
Preferred qualifications
Master's degree or PhD in Computer Science, or related technical field.
3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
1 year of experience in a technical leadership role.
Experience developing accessible technologies.
Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
Experience in Generative AI (Large Language Models, Multi-Modal, Large Vision Models).
Experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, natural language processing, or other ML disciplines.
