Cloud Engineer, AI/ML, Professional Services, Google Cloud

$171,000 - $257,000/Yr

Google - Boulder, CO

Full-time - Mid Level

Boulder, CO

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About the position

As a Cloud AI Engineer at Google Cloud, you will play a pivotal role in designing and implementing machine learning solutions tailored to customer use cases. This position involves leveraging core Google products such as TensorFlow, DataFlow, and Vertex AI to help businesses transform and evolve through cloud technology. You will work closely with customers to identify opportunities for machine learning applications, provide architecture guidance, and support the implementation of Google Cloud products, ensuring best practices and excellence in delivery.

Responsibilities

• Design and implement machine learning solutions for customer use cases using Google products.
• Work with customers to identify opportunities to apply machine learning in their business.
• Travel to customer sites to deploy solutions and deliver workshops.
• Support customer implementation of Google Cloud products through architecture guidance and best practices.
• Coach customers on practical issues in machine learning systems such as feature extraction and data validation.
• Create and deliver best practice recommendations, tutorials, and sample code.
• Collaborate with product management and engineering teams to drive product excellence.

Requirements

• Bachelor's degree in Computer Science or equivalent practical experience.
• 8 years of experience designing cloud enterprise solutions and supporting customer projects to completion.
• 8 years of experience building machine learning solutions and working with technical customers.
• Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++).

Nice-to-haves

• Experience working with recommendation engines, data pipelines, or distributed machine learning.
• Experience with deep learning frameworks (e.g., Tensorflow, pyTorch, XGBoost).
• Knowledge of data warehousing concepts and ETL/ELT processes.
• Understanding of practical concerns in production machine learning systems.

Benefits

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