Senior Software Engineer, Map Ads, Machine Learning
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
In this role, you will build the next generation of modeling and quality infrastructure for queryless ad formats—a complex space where user intent is implicit rather than stated. You will lead technical roadmaps across retrieval, auction, and measurement, utilizing techniques such as LLM-based distillation and differential modeling.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience programming in C++ and SQL.
- 3 years of experience with one or more of the following: reinforcement learning (e.g., sequential decision making), recommendations/ranking, LLMs, ML infrastructure, or specialization in another ML field.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
Preferred qualifications:
- Experience with working on Ads or product quality improvement areas.
- Experience with integrating new machine learning research techniques.
- Experience with working on ranking and retrieval models.