Customer Engineer, Applied and Generative AI, Google Cloud

Job Description

Customer Engineer, Applied and Generative AI, Google CloudLocation: Singapore; Jakarta, IndonesiaExperience Level: MidGoogle will be prioritizing applicants who have a current right to work in Singapore, and do not require Googles sponsorship of a visa.Note: By applying to this position, you will have an opportunity to share your preferred working location from the following: Singapore; Jakarta, Indonesia.Minimum qualifications:

• Bachelors degree or equivalent practical experience.
• 6 years of experience with cloud native architecture in a customer-facing or support role.
• Experience in pre-sales and consulting, delivering technical presentations, and leading discovery and planning sessions with customers with defined scope and success criteria.
• Experience with frameworks for deep learning (e.g. PyTorch, TensorFlow, Jax, Ray, etc.) and using machine learning APIs.

Preferred qualifications:

• Experience in building and deploying data and Machine Learning (ML) pipelines with a focus on automation.
• Experience with prompt tuning and delivering successful prototypes.
• Experience in building machine learning solutions and leveraging specific machine learning architectures (e.g. deep learning, LSTM, convolutional networks, etc.).
• Experience working in technology sales within the South East Asia region.
• Experience in understanding customers existing software workloads, and the ability to define a technical migration roadmap to the cloud reflecting specific customer needs.
• Ability to communicate in Bahasa Indonesia fluently to support client relationships in the region.

About the jobThe Google Cloud Platform team helps customers transform and build whats 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 how businesses of all sizes use technology to connect with customers, employees, and partners.As a Customer Engineer, you will partner with technical business teams as a subject matter expert in Artificial Intelligence and Machine Learning (AI/ML) to differentiate Google Cloud to the customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business tests, engage in proofs of concepts, and troubleshoot any technical questions and roadblocks. You will engage with customers to understand their business and technical requirements and persuasively present practical and useful solutions on Google Cloud. You will partner with internal engineering stakeholders to improve products and build solutions, optimize for results when in production, and identify innovative ways to multiply the impact of the team as a whole.Google Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Googles 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 the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
• Share in-depth AI/ML expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
• Work directly with Google Cloud products to demonstrate and prototype integrations in customer and partner environments.
• Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution on Google Cloud.
• Travel to customer sites, conferences, and other related events and act as a public advocate for Google Cloud.

Information collected and processed as part of your Google Careers profile and any job applications you choose to submit is subject to Googles Applicant and Candidate Privacy Policy. 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 Googles 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, to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.Locations: Singapore; Jakarta, IndonesiaExperience Level: MidExperience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within the relevant area.

Keyskills :
cloud native architecture machine learning apis technical presentations deep learning frameworks data pipeline automation production action alias prototype planning cutting