Cloud Engineer, AI, Google Cloud (google)

Qualifications

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
  
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• 3 years of experience building Machine Learning or Data Science solutions.
  
• Experience with data structures, algorithms, software design, and coding in Python, Scala, R, or similar.
  
• Ability to travel up to 30% of the time as needed.
  

Preferred qualifications:

• Experience working with recommendation engines, data pipelines, or distributed machine learning, data analytics, data visualization techniques and software, and deep learning frameworks.
  
• Experience in software development, professional services, solution engineering, technical consulting, architecting and rolling out new technology and solution initiatives.
  
• Experience with core Data Science techniques.
  
• Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT and reporting/analytic tools and environments.
  
• Knowledge of cloud computing, including virtualization, hosted services, multi-tenant cloud infrastructures, storage systems, and content delivery networks.
  
• Excellent customer-facing communication and listening skills.

Summary

• Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
  
• 3 years of experience building Machine Learning or Data Science solutions.
  
• Experience with data structures, algorithms, software design, and coding in Python, Scala, R, or similar.
  
• Ability to travel up to 30% of the time as needed.
  

Description

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 a Cloud Engineer, you'll ensure that customers have a good experience moving to the Google Cloud machine learning (ML) suite of products. You will design and implement machine learning solutions for customer use cases, leveraging core Google products. You'll work with customers to identify opportunities to transform their business with machine learning, and will travel to customer sites to deploy solutions and deliver workshops designed to educate and empower customers to realize the full potential of Google Cloud. You will have access to Google’s technology to monitor application performance, debug and troubleshoot product code, and address customer and partner needs. In this role, you will lead the timely execution of adopting the Google Cloud Platform solutions to the customer’s requirements.

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

• Deliver effective big data and machine learning solutions and solve complex technical customer challenges.
• Act as a trusted technical advisor to Google’s most strategic customers.
• Identify new product features and feature gaps, provide guidance on existing product challenges, and collaborate with Product Managers and Engineers to influence the roadmap of Google Cloud Platform.
• Deliver best practices recommendations, tutorials, blog articles, and technical presentations adapting to different levels of key business and technical stakeholders.

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