Cloud Solutions Engineer

1 week ago


Chicago, Illinois, United States Google Full time

Minimum qualifications:

Bachelor's degree in Computer Science or a related field, 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 processing pipelines, or distributed machine learning techniques.

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 analytics tools (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).

A comprehensive understanding of practical considerations in deploying machine learning systems in production environments.

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

We assist organizations in transforming and advancing their operations by leveraging Google's extensive network, large-scale data centers, and software infrastructure.

As part of a forward-thinking team in this rapidly expanding sector, you will contribute to shaping the future of businesses of all sizes, utilizing technology to engage with customers, employees, and partners.

In the role of Cloud AI Engineer, you will design and implement 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 applications in their operations, traveling to client sites to deploy solutions and conduct workshops that educate and empower them.

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

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


Together with your team, you will assist clients in implementing Google Cloud products through:

  • Architecture guidance
  • Best practices
  • Data migration
  • Capacity planning
  • Implementation
  • Troubleshooting
  • Monitoring

Google Cloud empowers organizations to digitally transform their operations and industries. We provide enterprise-grade solutions that utilize Google's innovative technology and tools, helping developers build sustainably.

Clients across more than 200 countries and territories rely on Google Cloud as their trusted partner to facilitate 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.

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 and definition
  • Data validation
  • Monitoring and management of features and models

Collaborate with clients, partners, and Google Product teams to deliver customized solutions into production.

Create and share best practice recommendations, tutorials, blog articles, and sample code.

Travel may be required for meetings, technical reviews, and onsite delivery activities.



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