Software Engineer, Workspace AI Platform Quality/Modeling Full-time

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in the Python programming language, and with data structures/algorithms.
• 2 years of experience with data structures or algorithms.
• 1 year of experience with core GenAI concepts (Large Language Models, Multi-Modal, Large Vision Models).
• 1 year of experience with machine learning infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Experience with text, image, video, or audio generation.

Preferred qualifications:

• Master’s degree or PhD in Computer Science or related technical field.
• Experience developing accessible technologies.

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 Gen AI models and infrastructure to build an intelligence platform to power Google Workspace products, such as Docs, 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 features that help users be their most creative, productive selves at work, school, and home.The web is what you make of it and our team is helping the world make more of the web. From open-source pros to user-experience extraordinaires, we develop products that help users connect, communicate and collaborate with others. Our consumer products and cloud platforms are giving millions of users at homes, businesses, universities and nonprofits around the world the tools that shape their web experience — and changing the way they think about computing.

The US base salary range for this full-time position is $136,000-$200,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

Responsibilities

• Write product or system development code.
• 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.
• Collaborate across multiple teams and function within Workspace as well as Gemini teams, to bring capabilities and quality improvements to various Workspace products.
• Implement GenAI solutions, utilize machine learning infrastructure, and contribute to data preparation, optimization, and performance enhancements.