Senior Software Engineer, Generative AI

Senior Software Engineer, Generative AI

corporate_fareGoogleplaceSunnyvale, CA, USA; New York, NY, USA

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with end-to-end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 1 year of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 5 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting.
• 5 years of experience with data structures and algorithms in either an academic or industry setting.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• 3 years of experience with ML/AI algorithms and tools, deep learning or natural language processing.

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.
The Workspace AI platform team uses Google's state-of-the-art Gen AI models and infrastructure to build an AI platform to power Google Workspace products, such as Google Documents, Sheets, Slides, Gmail, Google Drive, which are actively used by hundreds of millions of users that depend on us each day. We are helping users be more productive by automating repetitive tasks, surfacing new insights and visualizations, and making content creation, collaboration, and consumption even easier. We are responsible for agentic features that help users be their most creative, productive selves at work, school, and home.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.

Responsibilities

• 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.