Staff ML Engineer - Shopping Ads Relevance & ML Infra

Google; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google's software engineers develop the next-generation technologies that empower billions of users to connect, explore, and interact with information. We seek engineers who bring fresh ideas across information retrieval, distributed computing, large-scale system design, networking, data storage, security, AI, NLP, UI, and mobile.

You will work on a project critical to Google’s needs, with opportunities to switch teams as the business grows.

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 ML field or related areas.
• 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, and more, to predict and improve user experience on search ads.
• Train machine learning models and explore model features, architectures, and hyperparameters to improve model accuracy, especially Gemini models.
• Implement code and tests for model training and backend code for model serving and logging.
• Run ads experiments and develop experiment metrics; interpret metrics related to user experience and quality.
• Perform model, experiment, and human evaluation analyses, and build custom analysis tools as needed.

Skills

Python

C++

ML design

Leadership

Cross-functional

Education

Bachelor's degree

Master’s degree or PhD

Tools

REX

Job description

Google's software engineers develop the next-generation technologies that empower billions of users to connect, explore, and interact with information. We seek engineers who bring fresh ideas across information retrieval, distributed computing, large-scale system design, networking, data storage, security, AI, NLP, UI, and mobile.

You will work on a project critical to Google’s needs, with opportunities to switch teams as the business grows.