Google

Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 6 years of experience with machine learning model development and deployment, frameworks (e.g., PyTorch, Tensorflow, Jax, Ray, etc.), AI accelerators (e.g., TPUs, GPUs), model architectures (e.g., encoders, decoders, transformers), and using machine learning Application Programming Interface (APIs).
• 6 years of experience in working with technical customers.
• Experience with Python.
• Active U.S. Government Top Secret Clearance.
• Ability to travel up to 30% of the time.

Preferred qualifications:

• Experience in optimizing Large Language Model (LLMs) leveraging retrieval augmented generation (RAG) architectures and fine-tuning techniques.
• Experience in building solutions for National Security customers.
• Experience in working with multiple clouds.
• Experience in C++ programming language.
• Experience in Linux/Unix.
• Ability to lead design and implementation of AI-based solutions, web services, and debugging tools and experience containerizing ML workloads.

About the Job

In this role, you will guide National Security customers on how to configure and deploy their Artificial Intelligence (AI) and Machine Learning (ML) solutions. You will support customer implementations of Google Cloud products through architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, etc. You will consult with customers on how to design their AI and machine learning solutions including development and deployment of ML models. You will travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. You will work 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 $147,000-$216,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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

• Be a trusted technical advisor to customers and solve Machine Learning tests.
• Create and deliver recommendations, tutorials, blog articles, sample code, and technical presentations adapting to different levels of business and technical stakeholders.
• Work with Customers, Partners, and Google Product teams to deliver solutions into production.
• Coach customers on the practical tests in ML systems like feature extraction/feature definition, data validation, monitoring, and management of features/models.