Senior Software Engineer, Ads, ML Infrastructure

Google is seeking a Senior Software Engineer to join their Ads ML Infrastructure team, offering a competitive base salary range of $166,000-$244,000 plus bonus, equity, and benefits. This role combines software engineering expertise with machine learning infrastructure development, focusing on building and maintaining recommendation systems at scale.

The position requires a strong background in software development, with at least 5 years of experience in languages like Python and C++, along with deep knowledge of data structures and algorithms. The ideal candidate will have 3 years of experience with ML infrastructure and recommendation systems, demonstrating expertise in model deployment, evaluation, optimization, and data processing.

As part of Google's engineering team, you'll be working on critical projects that impact billions of users, developing next-generation technologies across various domains including information retrieval, distributed computing, and artificial intelligence. The role offers opportunities to switch teams and projects as both you and the business evolve.

Key responsibilities include writing and testing code, collaborating on design and code reviews, contributing to documentation, troubleshooting complex system issues, and designing recommendation systems across different domains. The position requires strong technical leadership qualities and the ability to tackle new challenges across the full stack.

Google offers a comprehensive benefits package and promotes an inclusive work environment, committed to building a diverse workforce representative of their global user base. The role provides the opportunity to work at either Pittsburgh, PA or Mountain View, CA locations, allowing flexibility in work location choice.

This is an excellent opportunity for experienced engineers who want to make a significant impact on Google's advertising infrastructure while working with cutting-edge ML technologies and recommendation systems at scale. The role combines technical depth with the breadth of Google's massive infrastructure, making it an ideal position for those looking to advance their careers in ML infrastructure and large-scale systems.