Staff ML Engineer, Shopping Ads: Relevance Models

Google; Town of Montana (WI); On-site; USD 207,000 - 300,000; Full time

Job summary

Google Mountain View is seeking an Staff ML Engineer for Search Ads Shopping Relevance Models. The role emphasizes owning outcomes, solving ambiguous problems, and influencing stakeholders with deep domain expertise.

You will lead ML design, deployment, and evaluation across ads, with strong Python/C++ coding and model-serving responsibilities. Responsibilities include improving user experience via modeling, experiments, and analytics, and collaborating with cross-functional teams.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience programming in Python or C++.
• 5 years of experience testing and launching software products.
• 5 years of experience leading ML design and optimizing ML infrastructure.
• 5 years of experience with one or more of: Speech/audio, reinforcement learning, ML infrastructure, or other ML field.
• 3 years of experience with software design and architecture.

Responsibilities

• Collaborate on user journey understanding, metric and label formulation, feature and model improvements, live traffic experiments, data analysis, tools and infrastructure.
• Train machine learning models and explore features, architectures, and hyperparameters to improve model accuracy, especially Gemini models.
• Implement code and tests for model training (Python, C++, on top of REX) and backend code for model serving (C++).
• Run ads experiments and develop experiment metrics; interpret a wide range of UX and quality metrics.
• Perform model, experiment, and human evaluation analyses and develop custom analysis tools if needed.

Skills

Python

C++

ML design

ML infrastructure

Software architecture

Reinforcement learning

Education

Bachelor's degree or equivalent practical experience

Master's degree or PhD (preferred)

Tools

REX

Job description

Google Mountain View is seeking an Staff ML Engineer for Search Ads Shopping Relevance Models. The role emphasizes owning outcomes, solving ambiguous problems, and influencing stakeholders with deep domain expertise.

You will lead ML design, deployment, and evaluation across ads, with strong Python/C++ coding and model-serving responsibilities. Responsibilities include improving user experience via modeling, experiments, and analytics, and collaborating with cross-functional teams.