Machine Learning Solutions Engineer, Cloud Learning Services

$142,000 - $211,000/Yr

Google - Sunnyvale, CA

Full-time - Mid Level

Sunnyvale, CA

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About the position

As a Machine Learning Solutions Engineer in Google Cloud Learning Services, you will focus on delivering, creating, and maintaining cutting-edge Machine Learning and Generative AI content. This role involves collaborating with cross-functional teams to enhance customer engagement and support their Machine Learning projects, ultimately helping to drive innovation and productivity through Google Cloud products.

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.

Requirements

• 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.

Nice-to-haves

• 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).

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• 401(k) plan
• Paid holidays
• Paid time off
• Employee stock purchase plan
• Tuition reimbursement
• Professional development opportunities