Software Engineer, App Ads Bidding and Optimization

Google•Mountain View, CA

2d•$147,000 - $210,000

About The Position

Google software engineers develop technologies that help billions of users connect, explore, and interact with information. This role works on a project important to Google, with opportunities to move between teams and projects as business needs evolve. Engineers are expected to bring fresh ideas, demonstrate leadership, and take on problems across the technology stack. Within Google Ads, the role contributes to AI-driven advertising technology, applying machine learning and generative AI to a global business. The work aims to protect users, improve ad quality, and optimize advertiser return on investment. The engineer will collaborate with teams such as Google Research and DeepMind on complex challenges at scale. The position focuses on improving app advertising bidding and optimization. Responsibilities include developing and evaluating statistical and machine-learning approaches, modernizing bidding infrastructure, improving campaign cold starts, and collaborating with product, UX, and partner teams to deliver advertising experiences.

Requirements

Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
At least 2 years of software development experience in one or more programming languages, or 1 year of experience with an advanced degree.
Experience in software development using C++.
Experience conducting quantitative data analysis, statistical modeling, and interpreting datasets.
Experience with mathematical optimization and statistical learning.

Nice To Haves

Experience in system design, including defining technical architecture, system interfaces, and data models.
Experience with programming languages used for data analysis and computational statistics, such as Python, R, MATLAB, C++, Java, or Go.
Experience with Colab, SQL, and other data analysis tools.
Experience with one or more of distributed and parallel systems, machine-learning models, information retrieval, or mathematical optimization techniques such as linear programming, convex optimization, or reinforcement learning.
Strong quantitative reasoning skills demonstrated in a mathematical field such as data science, optimization, machine learning, or natural science.

Responsibilities

Improve the accuracy and stability of the UAC bidder using statistical analysis and new machine-learning or optimization algorithms.
Improve and modernize bidding infrastructure, and design and implement bidding algorithms that enable faster cold starts for new campaigns.
Debug inaccuracies in bidding infrastructure; propose improvements and launch them through design, implementation, experimentation, and analysis.
Incorporate and engineer input features from ad creatives, publisher pages and content, and users’ personalized ad history to improve bidding and modeling accuracy.
Improve the efficiency and reliability of machine-learning models by designing novel model architectures and adopting robust development and release processes.
Debug and troubleshoot complex interactions between business goals, mathematical models, and infrastructure.
Work with product managers, UX, and partner teams to design and deliver new ad experiences.
Use data and metrics to evaluate product success and inform business decisions.