Minimum qualifications:
- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 5 years of experience in solution engineering and 3 years of experience in stakeholder management, professional services, or technical consulting.
- 3 years of experience in technical troubleshooting and writing code in one or more programming languages.
- Experience with all phases of a ML project delivery from data collection to production deployment at scale.
- Experience building technical solutions with AI technologies in a cloud environment.
- Master's degree in Engineering, Computer Science, or related technical fields.
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About the job
The Google Cloud Applied AI team focuses on innovating and developing industry solutions within top industries of cloud, including telecommunication, healthcare, retail, media, entertainment, finance, manufacturing, gaming, and public services. In this role, you will help customers transform and evolve their business through the use of Google's global network, web-scale data centers and software infrastructure. As part of an entrepreneurial team in this rapidly growing business, you will help shape the future businesses of all sizes using technology to connect with customers, employees and partners.
Google Cloud Risk AI within Applied AI is an entrepreneurial team building high-performance, highly-available platforms to support use cases like the detection of financial crime while also looking to bring new products to market.
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.
Responsibilities
- Solve complex customer use cases using Google Cloud products in concert with AI to drive customer adoption, create reusable assets (e.g. code, toolkits, training), and deliver training for new product features, or solutions for customers, partners, and field teams.
- Collaborate cross-functionallywith Google Cloud Applied AI teams (e.g. product, engineering, sales, professional services, etc).
- Discusses functional, technical, and basic commercial topics with customer stakeholders (e.g. developers, line managers) and is able to empathize, shape, and influence them.
- Work with customer stakeholders as a trusted advisor and provide expert guidance on critical solution decisions.