About the role
What will you do at Google?
MINIMUM QUALIFICATIONS:
* Bachelor's degree in Science, Technology, Engineering, Mathematics, or
equivalent practical experience.
* 8 years of experience in Python or other programming languages in machine
learning (e.g., Java, C++, Go).
* Experience in applied AI, with a focus on designing and evaluating systems
around foundation models (e.g., prompt engineering, fine-tuning, RAG,
orchestrating model interactions with external tools to deliver solutions).
* Experience architecting, deploying, or managing solutions on a cloud
platform.
* Active, or the ability to obtain, Top Secret/SCI security clearance.
PREFERRED QUALIFICATIONS:
* Master's degree in Computer Science, Engineering, or a related technical
field.
* Experience with distributed training and optimizing performance versus costs.
* Experience supporting or selling to U.S. federal customers.
* Experience in system design with the ability to architect and explain data
pipelines, ML pipelines, and ML training and serving approaches.
* Experience training and fine tuning models in environments (e.g., image,
language, recommendation) with accelerators.
* Ability to demonstrate a bias for action and apply product insights to solve
immediate customer issues and unlock long-term value.
ABOUT THE JOB:
As a Field Solutions Architect, you will support the Rapid Innovation team in
Google Public Sector. You will construct rapid prototype generative AI
applications tailored to public sector customers.
You will leverage generative AI technologies to develop innovative solutions and
validate their efficacy. You will swiftly showcase the latest generative AI
capabilities through direct collaboration with customers.
In this role, you will
- closely collaborate with our Product team to eliminate
- obstacles and shape the future trajectory of our offerings. In addition, you
- will disseminate the lessons learned to customers and internal Google teams.
- Google Public Sector
- [https://about.google/intl/ALL_us/public-sector/#:~:text=We're%20committed%20to%20advancing,%2C%20research%2C%20and%20edtech%20companies.]
- brings the magic of Google to the mission of government and education with
- solutions purpose-built for enterprises. We focus on helping United States
- public sector institutions accelerate their digital transformations, and we
- continue to make significant investments and grow our team to meet the complex
- needs of local, state and federal government and educational institutions.
- Individual pay is determined by factors including job-related skills,
- experience, and relevant education or training.
- US: $183000 - $266000 (USD) + 20% bonus target + equity + benefits
- Learn more about benefits at Google
- [https://www.google.com/about/careers/applications/benefits/].
- RESPONSIBILITIES:
- * Be a trusted advisor to customers by understanding their business process and
- objectives. Design and build end-to-end genAI-driven solutions spanning AI,
- data, and infrastructure.
- * Demonstrate how Google Cloud is differentiated by working with customers on
- application prototypes; demonstrating generative AI features; prompting and
- tuning models; and optimizing model performance, profiling, and benchmarking.
- Troubleshoot and find solutions to issues in generative AI applications.
- * Build repeatable technical assets such as scripts, templates, reference
- architectures, etc. to enable customers and internal teams. Work with peers
- to include the full cloud stack into overall architecture.
- * Work cross-functionally to influence Google Cloud strategy and product
- direction at the intersection of infrastructure and AI/ML by advocating for
- enterprise customer requirements.
- * Coordinate regional field enablement with leadership and work closely with
- product and partner organizations on external enablement. Travel as needed.
Which skills does this role require?
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- Practice explaining your experience in an interviewRehearse your answers before meeting the hiring team.
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Role information can change. Confirm current details on the original application page.
