Job Type
Job Details
- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 7 years of experience in a statistical programming language (e.g., Python).
- Experience in Artificial Intelligence applications (e.g., deep learning, natural language processing, computer vision, or pattern recognition), applied machine learning techniques, or using OSS frameworks (e.g., TensorFlow, PyTorch).
- Experience delivering technical presentations and leading business value sessions.
Preferred qualifications:
- Master's degree in Computer Science, Engineering, or a related technical field.
- Experience with CI/CD solutions in the context of ML Operations and Large Language Model (LLM) Operations including automation with IaC (e.g., Terraform).
- Experience in systems 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 large scale environments (e.g., image, language, recommendation) with accelerators.
- Experience with distributed training and optimizing performance versus costs.
As a Field Solutions Architect, you will play a pivotal role in supporting our Google Cloud sales organization. Your primary responsibility will be to construct rapid prototype Generative AI applications tailored to Google Cloud customers, catering to a diverse clients ranging from early stage startups to prominent companies.
In this role, 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 front 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 be able to grow in ambiguous situations. 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 $171,000-$257,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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.
- Be a trusted advisor to our customers by understanding the customer’s business process and objectives. Design Generative AI-driven solutions, spanning AI, Data, and Infrastructure, and work with peers to include the full cloudstack into overall architecture.
- Demonstrate how Google Cloud is differentiated by working with customers on application prototypes, demonstrating Generative AI features, prompting and tuning models, optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues in Generative AI applications.
- Build repeatable technical assets (i.e., scripts, templates, reference architectures, etc.) to enable customers and internal teams.
- 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.
