Machine Learning Solutions Engineer, Google Cloud Learning Services

Key Skills

Java Programming, Oracle, Python Programming, SQL, Apache Hadoop, Machine learning techniques, Google Cloud Platform (GCP), Scikit-learn, PostgreSQL, MySQL, MxNet, SPARK Programming, Splunk

Job Description

Minimum qualifications:

• Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.
• Experience building ML models for use cases, and software engineering experience building production ML models with TensorFlow, MXNET, Spark ML, and Scikit-learn, etc.
• Experience conducting data or ML technical training, or in a customer-facing technical consulting role.

Preferred qualifications:

• Master's or PhD degree in Computer Science, Mathematics, or a related quantitative field.
• Experience working in a technology area, while being comfortable working in a dynamic and sometimes ambiguous environment.
• Experience with databases, schema design, and data processing technologies (e.g., Hadoop, Spark, Splunk, etc.).
• Experience taking on materials and successfully delivering them to customers/students.
• Understanding in one or more SQL database technologies (e.g., PostgreSQL, MySQL, Oracle, MS SQL, etc.).
• Passion for learning and continued self-development.

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 listen to the customer and swiftly problem-solve technical issues 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 Cloud business and helping companies around the world innovate.

The Advanced Solutions Lab (ASL) for Machine Learning (ML) provides customers with the opportunity to work with Google’s Machine Learning experts in an immersive experience that enables companies to address their highest-impact business challenges.

As a Machine Learning Solutions Engineer, you will be focused on delivering and, at times creating, Machine Learning training for ASL participants. You will be working with customers as they explore how to apply Machine Learning to their specific business use cases. You will also manage the day-to-day experience of the Advanced Solutions Lab.

You will work to improve the offering such as recommendations on curriculum enhancements, identifying and engaging Google ML experts to support various sessions in the program, or making recommendations on pre-packaged ML models or projects for inclusion. You will also be a member of the wider Professional Service Organization (PSO) ML experts with the opportunity to work on customer-facing projects to help customers benefit from Google Cloud Machine Learning solutions.

Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology – all on the cleanest cloud in the industry. 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

• Manage the success of each ML Advanced Solutions Lab experience by delivering training, identifying ML experts across Google to support specific sessions, and providing ongoing curriculum feedback.
• Stay up-to-date on developments in ML and network across the Google Cloud ML research community, to provide ASL participants with up to date knowledge and unique opportunities for highly-interactive engagements with other Google ML experts.
• Support the Google Cloud Professional Services Machine Learning practice in the delivery of customer-facing services.
• Act as an ML subject matter expert within the Google Cloud Professional Services team and support other ML activities as they arise (e.g., work to develop IP, be a speaker at external events, run ML bootcamps).
• Deliver ML related Professional Services Organization offerings which may go beyond the scope of the services available.