Understanding of the auxiliary practical concerns in production Machine Learning (ML) systems.

About the job

The Google Cloud Platform team helps customers transform and build what's next for their business - all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers - developers, small and large businesses, educational institutions and government agencies - see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As an AI Consultant, you will work directly with customers on critical projects to help them transform their businesses using AI/ML technologies. You will help them develop, deploy, and manage custom AI solutions in production using Google Cloud technologies. You will provide technical project management, consulting and technical aptitude to customer engagements while working with client executives and key technical leaders to deploy solutions via Google's Cloud Platform. You will also work closely with key Google partners on accounts to scope engagements, manage programs, deliver consulting services, and provide technical guidance, and best practice expertise.

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

• Work with customer technical leads, client executives, and partners to scope, manage, and deliver successful implementations of cloud solutions becoming a trusted advisor todecisionmakers throughout the engagement.
• Work with internal specialists, Product and Engineering teams to package best practices and lessons learned into thought leadership, methodologies, and published assets.
• Interact with sales, partners, and customer technical stakeholders to manage project scope, priorities, deliverables, risks/issues, and timelines for successful client outcomes. Advocate for customer needs in order to overcome adoption blockers and drive new feature development based on your field experience.
• Propose solution architectures and manage the deployment of cloud based machine learning solutions according to complex customer requirements and implementation best practices.
• Travel approximately 30% of the time for client engagements.