AI Engineer, Google Professional Services at Google EMEA

Qualifications

Minimum qualifications:
  • Bachelor's degree in Computer Science, Mathematics, related technical field, or equivalent practical experience.
  • Experience writing software in one or more languages such as Python, Scala, R, etc.
  • Experience building Machine Learning (ML) solutions, working with data structures, algorithms, and software design.
  • Experience working with customers and management.

Preferred qualifications:
  • Experience working with recommendation engines, data pipelines, and/or distributed ML.
  • Experience with deep learning frameworks (such as l, Torch, Caffe, Theano).
  • Experience in technical consulting.
  • Understanding of the auxiliary practical concerns in production ML systems.
  • Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT, and reporting/analytic tools and environments (such as Apache Beam, Hadoop, Spark, Pig, Hive, etc.).

About the job


The Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You swiftly problem-solve technical issues for customers to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its Google Cloud business and in bringing our product portfolio into companies around the world.
Google Cloud helps millions of employees and organizations empower their employees, serve their customers, and build what’s next for their business — all with technology built in the cloud. Our products are engineered for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. And 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.

Responsibilities


  • Be a trusted technical advisor to customers and solve complex ML challenges.
  • Create and deliver best practices recommendations, tutorials, blog articles, sample code, and technical presentations, adapting to different levels of key business and technical stakeholders.
  • Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
  • Coach customers on the practical challenges in ML systems including feature extraction/feature definition, data validation, monitoring, and management of features/models.
  • Travel regularly (up to 30%) in-region for meetings, technical reviews, and onsite delivery activities.

Location


 
 
 
 
 
 
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Map data ©2021 Google
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