Ai/ml Field Solutions Architect
4 days ago
**Minimum qualifications**:
- Bachelor's degree in Computer Science, Data Science, or equivalent practical experience.
- 4 years of experience working in AI/ML as a technical sales engineer or in software engineering.
- Experience with Python and ML frameworks (e.g., TensorFlow, PyTorch).
- Experience delivering technical presentations and leading business value sessions.
- Generative AI experience as a user or a developer.
**Preferred qualifications**:
- Experience designing and deploying with one or more from the following ML frameworks: TensorFlow, PyTorch, JAX, Spark ML, etc.
- Experience training and fine tuning models in large-scale environments (i.e., image, language, recommendation) with accelerators.
- Experience with distributed training and optimizing performance versus costs.
- Experience with CI/CD solutions in the context of MLOps and LLMOps, including automation with IaC (e.g. using terraform).
- Experience in systems design with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches.
**About the job**:
As an AI/ML Field Solutions Architect, you will support Google Cloud sales teams and engineering incubate, pilot, and deploy Google Cloud’s industry leading AI/ML and GenAI technology at AI natives and innovators, large enterprises, and early stage AI startups. You will help customers innovate faster with solutions using Google Cloud’s flexible and open infrastructure including AI Accelerators.
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.
**Responsibilities**:
- Be a trusted advisor to our customers by understanding the customer’s business process and objectives. Architect AI-drive spanning data, AI and infrastructure, and work with peers to include the full Cloud stack into overall architecture.
- Demonstrate how Google Cloud is differentiated by working with customers on POCs, demonstrating features, tuning models, optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues on training/serving models in a large-scale environment.
- Build repeatable technical assets such as scripts, templates, reference architectures, etc. to enable other 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 activities.
- Travel as needed.
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.
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