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Cloud Solutions Engineer

2 months ago

Chicago, Illinois, United States Google Full time

Minimum qualifications:

A 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 frameworks.

Familiarity with deep learning libraries (e.g., TensorFlow, PyTorch, XGBoost). Understanding of data warehousing concepts, including technical architectures, infrastructure components, ETL/ELT processes, and reporting/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.

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 clients to innovate and evolve their operations through the utilization of Google's extensive network, scalable data centers, and robust software infrastructure.

As a member of a dynamic team in this rapidly expanding sector, you will influence the future of organizations of all sizes, leveraging technology to engage with customers, employees, and partners.

In the capacity of a Cloud AI Engineer, you will architect and implement machine learning solutions tailored to client needs, utilizing core Google technologies such as TensorFlow, DataFlow, and Vertex AI.

Your role will involve collaborating with clients to uncover opportunities for machine learning applications in their businesses, along with traveling to client locations to deploy solutions and conduct workshops aimed at educating and empowering clients.

Moreover, you will work in close partnership with Product Management and Product Engineering teams to enhance and drive excellence in our offerings.

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


Together with your team, you will support 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 operations and industry. We provide enterprise-grade solutions that leverage Google's advanced technology and tools, assisting developers in building more sustainably.

Clients across more than 200 countries and territories rely on Google Cloud as their trusted partner to foster growth and address their most pressing business challenges.

Compensation: The base salary range for this full-time position is $142,000-$211,000, in addition to bonuses, equity, and benefits. Our 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, definition, validation, monitoring, and management of features and models.
- Collaborate with Clients, Partners, and Google Product teams to deliver customized solutions into production.
- Develop and present best practice recommendations, tutorials, blog articles, and sample code.
- Travel up to 30% for meetings, technical reviews, and onsite delivery activities.