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Cloud Solutions Engineer

2 months ago

Chicago, Illinois, United States Google Full time

Minimum qualifications:

Bachelor's degree in Computer Science or equivalent practical experience. A minimum of 5 years of experience in developing machine learning solutions and collaborating with technical clients.

Proven experience in designing enterprise cloud solutions and guiding customer projects to successful completion.

Proficiency in one or more programming languages (e.g., Python, Java, Go, C or C++) with a solid understanding of data structures, algorithms, and software design principles.


Preferred qualifications:

Experience with recommendation systems, data pipelines, or distributed machine learning architectures.

Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, XGBoost) and knowledge of data warehousing concepts, including technical architectures, infrastructure components, ETL/ELT processes, and reporting/analytic tools (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).

A comprehensive understanding of the practical challenges associated with deploying machine learning systems in production environments.

About the role: The Google Cloud Consulting Professional Services team assists clients during critical phases of their cloud transformation journey, enabling businesses to thrive.

We empower organizations to evolve through the utilization of Google's extensive global network, large-scale data centers, and advanced software infrastructure.

As part of a forward-thinking team in this rapidly expanding sector, you will play a key role in shaping the future of businesses of all sizes, leveraging technology to enhance connections with customers, employees, and partners.

As a Cloud AI Engineer, your responsibilities will include designing and implementing machine learning solutions tailored to customer use cases, utilizing core Google products such as TensorFlow, DataFlow, and Vertex AI.

You will collaborate with clients to identify opportunities for machine learning integration into their operations, and may travel to client locations to deploy solutions and conduct workshops aimed at educating and empowering clients.

Additionally, you will work closely with Product Management and Product Engineering teams to continuously enhance our offerings.

In this capacity, you will serve as a Google Engineer, collaborating with some of the largest and most ambitious Cloud clients.


Together with your team, you will facilitate the implementation of Google Cloud products through:

  • Architectural guidance
  • Best practices
  • Data migration
  • Capacity planning
  • Implementation
  • Troubleshooting
  • Monitoring
  • And much more.

Google Cloud accelerates every organization's capacity to digitally transform its business and industry. We provide enterprise-grade solutions that leverage Google's state-of-the-art technology, along with tools that assist developers in building more sustainably.

Organizations in over 200 countries and territories rely on Google Cloud as their trusted partner to foster growth and address their most pressing business challenges.

Compensation: The US base salary range for this full-time position is $142,000-$211,000, plus bonus, equity, and benefits. Salary ranges are determined by role, level, and location.

The displayed range reflects the minimum and maximum target for new hire salaries for the position across all US locations. Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

For more information about benefits at Google, please refer to our resources.

Responsibilities:

  • Act as a trusted technical advisor to clients, addressing complex machine learning challenges.
  • Guide clients on practical issues in machine learning systems, including feature extraction, data validation, and model management.
  • Collaborate with Clients, Partners, and Google Product teams to deliver customized solutions into production.
  • Create and disseminate best practice recommendations, tutorials, blog articles, and sample code.
  • Travel up to 30% for meetings, technical reviews, and onsite delivery activities.