Wholepage Optimization Software Engineer, Ads

About The Job

Google's software engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information. This role focuses on the Wholepage Optimization Software Engineer position within Google Ads, a team at the intersection of user intent and monetization on search. The team leverages cutting-edge machine learning and LLMs to reimagine the commercial journey across Google Search and Lens, aiming to deliver value to users, advertisers, and Google's long-term revenue. Google Ads is at the forefront of AI innovation, applying machine learning and Generative AI models like Gemini to power a multi-billion dollar global business. The work directly impacts billions of users by protecting them from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. The team fosters deep collaboration with groups like Google Research and DeepMind.

Key Responsibilities

• Leverage state-of-the-art AI/ML advancements, including LLMs & Agentic AI, to solve critical optimization problems across search ads, from product innovation to agentic automation.
• Drive 10x better ads experiences compared to current offerings in the world of AI.
• Identify gaps in existing engineering processes and solve them using AI-driven automation.
• Design, build, and maintain self-service tools and platform features that embed advanced AI/ML quality evaluation methods.
• Architect scalable systems for deploying and serving AI/ML models specifically for data quality assessment tasks.
• Design, develop, test, deploy, maintain, and enhance software solutions.
• Manage project priorities, deadlines, and deliverables.

Requirements & Tech Stack

• Experience programming in Python or C++.
• Experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
• Experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• Experience with data structures and algorithms.
• Experience developing accessible technologies.
• Experience in Search/Ads or general quality systems.
• Familiarity with the latest research and trends in AI/ML, particularly as applicable to data quality and assessment.
• Expertise in full-stack engineering and app development.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience programming in Python or C++.
• 1 year of experience with end-to-end Machine Learning.
• 1 year of experience with one or more of the following: Speech/audio, reinforcement learning, ML infrastructure, or specialization in another ML field.
• Preferred: Master's degree or PhD in Computer Science or related technical field.
• Preferred: 2 years of experience with data structures and algorithms.
• Preferred: Experience developing accessible technologies.
• Preferred: Experience in Search/Ads or general quality systems.
• Preferred: Familiarity with the latest research and trends in AI/ML.
• Preferred: Expertise in full-stack engineering and app development.