Staff Software Engineer, Ads Content Safety

Google•Mountain View, CA

3d•$207,000 - $300,000

About The Position

Google is hiring a Staff Software Engineer for Google Ads Content Safety. The role focuses on building next-generation advertising technology using AI and machine learning to protect users from harm, improve ad quality, and optimize advertiser return on investment. The engineer will work on policy enforcement and consumer trust systems at massive scale, collaborating with teams including Google Research and DeepMind. The position calls for technical leadership, full-stack software development, and work integrating generative AI and LLM solutions.

Requirements

Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience testing and launching software products.
5 years of experience with full-stack development across back-end codebases such as Java, Python, Golang, or C++, and front-end technologies including JavaScript or TypeScript, HTML, CSS, or equivalent.
3 years of experience with software design and architecture.
Experience integrating generative AI tools or LLM interfaces into workflows.

Nice To Haves

5 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure, such as model deployment, model evaluation, data processing, debugging, or fine-tuning.
5 years of experience with reinforcement learning, ML infrastructure, or specialization in another ML field.
Experience with Generative AI, LLMs, prompt engineering, and model distillation techniques, or the ability to rapidly master and guide team architectures in these areas.
Excellent communication skills working with cross-functional partners, privacy, and legal.

Responsibilities

Define technical roadmaps and deliver models and agents to automate policy enforcement, improve velocity, and reduce user harm.
Drive rapid prototyping and experimentation on architectural options for next-generation consumer trust enforcement using AI and LLM solutions.
Identify and implement architecture improvements to build multi-tiered systems that manage massive query volumes and resolve complex policy cases.
Design, develop, test, deploy, maintain, and enhance large-scale software solutions.
Provide technical leadership, mentor distributed engineering teams, and facilitate alignment on goals, outcomes, and timelines.