Machine Learning Solutions Engineer, Cloud Learning Services

Key Skills

Aartificial intelligence, C++, JavaScript, Machine learning techniques, Natural Language Processing (NLP), Python Programming

Job Description

Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 6 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
• Experience in technical troubleshooting, and managing internal/external partners or customers.
• Experience building ML models for different use cases and conducting ML technical training.

Preferred qualifications:

• Master’s degree in Engineering, Computer Science, Business, or a related field.
• Experience in an analytical role such as business intelligence, data analytics, or statistics.
• Experience with cloud technologies such as architecting, developing, or maintaining cloud solutions in virtualized environments or cloud data engineering.
• Experience using Machine Learning and building solutions.
• Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT, and reporting/analytic tools and environments (Apache Beam, Hadoop, Spark, Hive).

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.

Cloud Learning Services (CLS) is revolutionizing cloud learning. We empower users of all levels with interactive labs and guided experiences to build practical skills on Google Cloud Platform and other leading technologies. Our mission is to make the cloud accessible, engaging, and enjoyable to learn.

As a Machine Learning Solutions Engineer, you will be focused on delivering, creating, and maintaining cutting-edge Machine Learning and Generative AI content. You will have the opportunity to collaborate and work on cutting-edge research and engineering projects and on customer engagements that deliver real impact on the world.

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.

The US base salary range for this full-time position is $142,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Own the success of each ML Advanced Solutions Lab experience by delivering excellent content, identifying ML experts across Google to support specific sessions and providing ongoing curriculum enhancements.
• Lead and support customers' Machine Learning projects from project framing to implementation in the Advanced Solutions Lab.
• Design AI/ML curriculum by understanding market and customers’ needs, and develop materials collaborating with the team and AI/ML experts across Google.
• Be informed of 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.
• Act as an ML SME within the Google Cloud Consulting team and support other ML activities.