GenAI ML Engineer — Cloud Data Management

Google; United States; On-site; USD 147,000 - 210,000; Full time

Job summary

Google Cloud Data Management is seeking a Software Engineer III for GenAI/AI-ML work in Mountain View, CA. You will develop scalable GenAI features, participate in cross-team collaboration, and help deploy ML pipelines within Google’s data management stack.

You will write production code, conduct design reviews, and contribute to documentation while optimizing data processing and model performance for large-scale services.

Qualifications

• Bachelor's degree or equivalent practical experience required.
• 2 years of experience programming in Python or C++.
• 1 year of experience with ML infrastructure (model deployment, evaluation, optimization, data processing, debugging).
• Experience with GenAI concepts (LLM, Multi-Modal, Large Vision Models) and with text, image, video, or audio generation.

Responsibilities

• Write product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.

Skills

Python

C++

GenAI concepts

ML infrastructure

Education

Bachelor's degree or equivalent

Master's degree or PhD

Job description

Google Cloud Data Management is seeking a Software Engineer III for GenAI/AI-ML work in Mountain View, CA. You will develop scalable GenAI features, participate in cross-team collaboration, and help deploy ML pipelines within Google’s data management stack.

You will write production code, conduct design reviews, and contribute to documentation while optimizing data processing and model performance for large-scale services.