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Field Solutions Architect, Generative AI, Google Cloud

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Field Solutions Architect, Generative AI, Google Cloud

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Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
This role may also be located in our Playa Vista, CA campus.
The application window will be open until at least August 1, 2025. This opportunity will remain online based on business needs which may be before or after the specified date.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Atlanta, GA, USA; Boulder, CO, USA; Cambridge, MA, USA; Addison, TX, USA; Los Angeles, CA, USA; Miami, FL, USA; Mountain View, CA, USA; Reston, VA, USA; Seattle, WA, USA; San Francisco, CA, USA; Sunnyvale, CA, USA; Washington D.C., DC, USA .Minimum qualifications:

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

Preferred qualifications:

• 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, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).
• Understanding of the auxiliary practical concerns in production machine learning systems.
  

About the job The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.
As a Generative AI Field Solutions Architect, you will play a pivotal role in supporting our Google Cloud sales organization.You will be responsible to construct rapid prototype Generative AI applications tailored to Google Cloud customers, catering to a clientele ranging from early stage startups to prominent Fortune 500 companies. You will leverage the latest Generative AI technologies to develop innovative solutions and validate their efficacy. You will be tasked with swiftly showcasing the latest Generative AI capabilities through direct collaboration with customers. You will be instrumental in materializing functional solutions on the Google Cloud platform.
Being at the forefront of expanding the boundaries of our Generative AI technology, you will have close collaboration with our product team to eliminate obstacles and shape the future trajectory of our offerings. You will possess a hacker's mindset and grow in ambiguous situations, as much of your work will be groundbreaking and uncharted. Additionally, you will be adept at disseminating the lessons learned to customers and internal Google teams.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $177,000-$263,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
Responsibilities

• Be a trusted technical advisor to customers and solve complex machine learning challenges.
• Coach customers on the practical challenges in machine learning systems, feature extraction and feature definition, data validation, monitoring, and management of features and models.
• Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
• Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
• Travel up to 30% as needed for in-region for meetings, technical reviews, and onsite delivery activities.
  
  

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Project Management, Consulting, and Engineering

• Industries

  Information Services and Technology, Information and Internet

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