As Director, you will be responsible for leading Google’s AI collection tooling strategy and roadmaps for Generative AI. You’ll be responsible for enabling developers for Google Products and external developers on Google Cloud to take a Data-centric approach to AI development, driving advances in model quality with tools that enable efficient, cost effective, and privacy-preserving data generation, collection, and sharing processes. You’ll be responsible for keeping a pulse on industry developme... more details
As Director, you will be responsible for leading Google’s AI collection tooling strategy and roadmaps for Generative AI. You’ll be responsible for enabling developers for Google Products and external developers on Google Cloud to take a Data-centric approach to AI development, driving advances in model quality with tools that enable efficient, cost effective, and privacy-preserving data generation, collection, and sharing processes. You’ll be responsible for keeping a pulse on industry developments, while deeply embedding alongside both research and product partners to help launch data tooling for generative AI. You will be responsible for intimately understanding the user journey across our internal and external customers, mapping pain points, and distilling user requirements and product feedback into long-term strategic roadmaps, identifying product features that add value and build trust with our customers.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge 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.
The US base salary range for this full-time position is $253,000-$363,000 + 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.
- Understand workflows for creators and consumers of large models, identifying opportunities to create privacy-preserving tooling that improve model and data quality.
- Define and deliver the Google-wide strategy for human data operations and tooling to improve data quality for Generative AI human data, reduce Operational Expenditure spend, and ensure IP protection and user privacy preservation.
- Drive the development of next-generation data tools for synthetic data and collection and ingestion of human feedback data.
- Partner with Google Research and Google DeepMind to identify new data tools and techniques. Conduct market assessments of new innovations in generative AI tooling, stay on top of emerging technologies and workflows, and learn from best practices in the industry.
- Work closely with all Google product areas to understand user requirements for data generation, collection, sharing, and ingestion for generative AI development.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 15 years of product management experience with technical products.
- Experience working with cross-functional teams
- Experience driving elements of the product development lifecycle such as product proposal, go-to-market strategy, driving requirements, product launch and driving adoption
Preferred qualifications:
- Experience working with developers who are building generative AI products
- Experience partnering with researchers to build applied ML products
- Experience building a platform for multiple groups of users with competing requirements
- Experience product managing internal ML infrastructure, advocating for its use cases, and growing its adoption