AI Engineer, Professional Services, Google Cloud

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 engineered 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 Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and AI Platform. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.

In this role, you will be in Engineering working with Google's Cloud customers. With the team, you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.

Google Cloud provides organizations with leading infrastructure, platform capabilities and industry solutions. We deliver enterprise-grade cloud solutions that leverage Google’s cutting-edge technology to help companies operate more efficiently and adapt to changing needs, giving customers a foundation for the future. Customers in more than 150 countries turn to Google Cloud as their trusted partner to solve their most critical business problems.

Responsibilities

• Be a trusted technical advisor to customers and solve complex machine learning (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: 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.

Minimum qualifications

• Bachelor's degree in Computer Science, Mathematics, or a related technical field, or equivalent practical experience.
• Direct experience building machine learning solutions.
• Experience coding in one or more languages (such as Python, Scala, Java, Go, or similar) with experience in data structures, algorithms, and software design.
• Experience working with technical customers.

Preferred qualifications

• Experience working with recommendation engines, data pipelines, or distributed Machine Learning.
• Relevant experience in technical consulting.
• Experience with deep learning frameworks (such as l, Torch, Caffe, Theano).
• 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, MapReduce, Flume).
• Understanding of the auxiliary practical concerns in production ML systems.