Customer Engineer, AI/ML, Google Cloud
Onsite
United StatesNew York City, NY, United StatesAtlanta, GA, United StatesAustin, TX, United States
United States
Full Time Posted 12 days ago
Job Type
Full Time
Job Details
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Atlanta, GA, USA; Austin, TX, USA; Cambridge, MA, USA; Chicago, IL, USA; Addison, TX, USA; Reston, VA, USA; Washington D.C., DC, USA. Minimum qualifications:
- Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
- 3 years of experience building or leveraging machine learning solutions and developing applications utilizing AI frameworks and methods.
- 3 years of experience as a technical sales engineer in a cloud computing environment or customer-facing role.
- Master's degree in Computer Science or a related technical field.
- Experience in data and information management as it relates to big data trends and issues within businesses.
- Experience building machine learning solutions and leveraging specific machine learning architectures (e.g., deep learning, LSTM, convolutional networks).
- Experience architecting and developing software or infrastructure for scalable distributed systems.
- Ability to learn, understand, and work with new emerging technologies, methodologies, and solutions in the Cloud/IT technology space.
- Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
- Provide in-depth machine learning expertise to support the technical relationship with Google’s customers, including product and solution briefings, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
- Work with customers to demonstrate and prototype Google Cloud product integrations in customer/partner environments.
- Recommend integration strategies, enterprise architectures, platforms and application infrastructure required to successfully implement a complete solution using best practices on Google Cloud.
- Travel to customer sites, conferences, and other related events as required.
Learn more about Google Inc.
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