Software Engineer III, AI/ML GenAI, Google Ads

Google•Mountain View, CA

8h•$147,000 - $210,000

About The Position

Google software engineers develop technologies used at massive scale across products that help people connect, explore, and interact with information. Engineers work on projects critical to Google’s needs and may have opportunities to switch teams and projects as the business evolves. The role calls for versatility, leadership qualities, and enthusiasm for solving problems across the full stack. This position is on Google Ads, where AI and machine learning models, including Generative AI models such as Gemini, support a global advertising business. The work affects users by helping protect them from harm, improve ad quality, and optimize advertiser campaign return on investment. The team collaborates closely with groups including Google Research and DeepMind to address complex challenges and develop advertising technology at scale. The Software Engineer will write product or system development code, implement GenAI solutions, use ML infrastructure, and contribute to data preparation, optimization, and performance improvements. The role also involves design and code reviews, maintaining documentation or educational content, and triaging and resolving product or system issues.

Requirements

Bachelor’s degree or equivalent practical experience.
At least 2 years of experience programming in Python or C++.
At least 1 year of experience with end-to-end machine learning, such as model deployment, model evaluation, data processing, or debugging.
Experience with core GenAI concepts, including LLMs, multimodal systems, or large vision models, and experience with text, image, video, or audio generation.

Nice To Haves

Master’s degree or PhD in Computer Science or a related technical field.
At least 2 years of experience with data structures and algorithms.
Experience developing accessible technologies.

Responsibilities

Write product or system development code.
Collaborate with peers and stakeholders through design and code reviews to uphold best practices, including style guidelines, code submission, accuracy, testability, and efficiency.
Contribute to existing documentation or educational content and adapt it based on product or program updates and user feedback.
Triage product or system issues and debug, track, and resolve them by analyzing causes and effects on hardware, network, or service operations and quality.
Implement GenAI solutions, use ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.