Minimum qualifications:
- Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 6 years of experience working with machine learning or deep learning systems.
- 6 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
- Experience in technical troubleshooting, and managing internal/external partners or customers.
- Active US Government Top Secret/Sensitive Compartmented Information (TS/SC) Security Clearance.
- Experience in optimizing Large Language Models (LLMs) leveraging RAG/retrieval augmented generation architectures and fine-tuning techniques.
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About the job
As a Cloud Artificial Intelligence/Machine Learning (AI/ML) Engineer, you will guide governments, universities, and other public sector customers on how to configure and deploy their virtual agents and machine learning solutions. Together with the team, you will support customer implementations of Google Cloud products through architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and more. You will consult with customers on how to best design their conversational AI and machine learning solutions including intent development, CI/CD, pipeline design, and training and evaluation of Machine Learning models. You will travel to customer sites up to 30% of the time to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to drive excellence in Google Cloud products and features.
Google Public Sector 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.
The US base salary range for this full-time position is $142,000-$211,000 + 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.
Responsibilities
- Serve as a trusted technical advisor to customers and solve complex Machine Learning problems.
- 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 Machine Learning systems: feature extraction/feature definition, data validation, monitoring, and management of features/models.