Principal Engineer, AI Data
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Minimum qualifications:
- Bachelor's degree in Computer Science, Software Engineering, similar technical field, or equivalent practical experience.
- 15 years of professional experience in software development.
- Experience with large-scale machine learning systems.
- Experience with large-scale ML infrastructure, ML or AI for products, or related fields.
Preferred qualifications:
- Experience building ML infrastructure or products with heavy use of AI/ML and large groups of stakeholders or users.
- Experience with Responsible AI.
- Experience with working with stakeholders to understand their needs and translate them into technical requirements.
- Experience working across highly horizontal areas requiring a high-degree of cross-organizational collaboration and coordination.
- Understanding of ML Systems and infrastructure for production with technical knowledge to be credible with customers and engineers.
About the job
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 $278,000-$399,000 + 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
- Drive the technical vision and execution of our AI Data Strategy, ensuring alignment with broader company goals.
- Architect and implement solutions across key areas, including data governance, responsible AI, human data operations, data acquisition, generation, ML developer toolkit, data quality and observability, and content ecosystem development.
- Define and implement technical architecture for ML data solutions, including tools, technologies, and frameworks.
- Collaborate effectively with diverse teams across Google, including product areas, research teams, infrastructure teams, and data governance and compliance teams.
- Influence and persuade stakeholders using technical expertise, judgment, and effective communication.
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Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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