Google Public Sector needs a Cloud Artificial Intelligence/Machine Learning (AI/ML) Engineer to guide Public Sector customers on how to configure and deploy their AI and machine learning solutions, and to support customer implementations of Google Cloud products.
Requirements
- Experience with machine learning model development and deployment working with technical customers.
- Experience with one or more programming languages, with a focus on Python.
- Experience with Large Language Models (LLMs) and LLM-based solutions such as prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG) workflows, and agentic systems.
- Experience containerizing ML workloads.
- Experience in Linux/Unix and C++ programming language.
- Experience working in multiple cloud environments.
- Ability to lead the design and implementation of AI-based solutions, web services, and debugging tools.
Responsibilities
- Translate business requirements into conceptual, logical, and physical data models.
- Create and deliver best practices recommendations, tutorials, blog articles, sample code, and technical presentations, adapting to different levels of key business and technical stakeholders.
- Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
- Coach customers on the practical challenges in ML systems: feature extraction/feature definition, data validation, monitoring, and management of features/models.
- Support customer implementations of Google Cloud products through architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and more.
- Consult with customers on how to best design their AI and machine learning solutions including development and deployment of ML models.
- Deploy solutions and deliver workshops to educate and empower customers.
Other
- Must be a US Citizen to meet customer and compliance requirements, including potential access to classified information.
- Bachelor's degree in Computer Science or equivalent practical experience.
- Active, or the ability to obtain, a Top Secret/SCI security clearance.
- Travel regularly (up to 30%) for meetings, technical reviews, and onsite delivery activities as needed.
- 3 years of experience with machine learning model development and deployment working with technical customers.
