Distinguished Engineer, Workspace AI - Google
Sunnyvale, CA
About the Job
Minimum qualifications:
- Bachelor’s degree in Computer Science, or similar technical field of study, or equivalent practical experience.
- 15 years of experience in software engineering or 13 years with an advanced degree.
- Experience in AI and machine learning, including generative AI and LLMs.
- Experience in evaluating and improving quality for generative AI models.
- Experience driving the technical direction and building confidence in the team and the team’s work.
Preferred qualifications:
- Experience as a thought Leader in AI, including experience with technology innovation and delivering business value.
- Knowledge of and strong point of view on technology leadership, research, and industry trends.
About the job
The Workspace Intelligence team is responsible for delivering exceptional ML-based features for users across Workspace, including Meet, Chat, Gmail, Drive, and Docs. One of Workspace’s key differentiators is Google’s strength in Machine Learning, which we use to build assistive features that help our customers be more productive. In the last few years, features like Help me Write, Help me Organize, Smart Compose, Smart Canvas, Docs Grammar, Sheets Smart Fill, and auto-captioning in Meet have changed the way the world gets things done. We imagine a future where content generation is effortless, where content is organized, classified, and summarized automatically and presented dynamically, where finding is made trivial by surfacing the right content just when it is needed, and where meeting notes write themselves so participants can stay focused on the conversation.
As a Distinguished Engineer for Workspace AI, you will be responsible for the technical architecture and systems to deliver features powered by AI throughout the Workspace products. You will deliver infrastructure, tooling, and processes that enable high impact ML features at a fast time-to-market with high quality while honoring data governance requirements. You will partner with other Google machine learning experts and researchers to ensure Workspace is using the best technology available, including applying state-of-the-art research ideas. You will work cross-functionally to execute the architecture and enable feature launches across Gmail, Calendar, Chat, Meet, Drive, Docs, Sheets, Slides, and more. You will be responsible for technical guidance and architecture across thousands of engineers, working closely with Product Engineers across Workspace.
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 $323,000-$465,000 + 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
- Lead the technical long-term strategy for Workspace AI while working directly to deliver infrastructure, tools, processes, and features at the highest level of technical excellence and quality.
- Build deep partnerships across Google and incorporate the best technology for Workspace AI with awareness of research and industry trends.
- Support our technical teams in delivering our roadmap on committed timelines.
- Identify high-value areas for investment and build execution paths to bring them to market.