GenAI ML Systems Engineer — Scale AI Solutions

Google; Mountain View (CA); On-site; USD 147,000 - 211,000; Full time

Job summary

Google Mountain View is seeking a software engineer to work on large-scale systems and AI-powered products. You will contribute to project ownership, write code, and collaborate across teams to deliver reliable services at scale.

You will explore GenAI features, run ML experiments, and help deploy models while maintaining quality, performance, and security across the Google Ads platform and related products.

Qualifications

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

ML infrastructure

GenAI concepts

Education

Bachelor's degree or equivalent practical experience

Job description

Google Mountain View is seeking a software engineer to work on large-scale systems and AI-powered products. You will contribute to project ownership, write code, and collaborate across teams to deliver reliable services at scale.

You will explore GenAI features, run ML experiments, and help deploy models while maintaining quality, performance, and security across the Google Ads platform and related products.