Senior Software Engineer - App Ads ML Modeling

Google LLC; Mountain View (CA); On-site; USD 147,000 - 210,000; Full time

Job summary

Google Mountain View, CA invites a Software Engineer III to join the App Ads Horizontal Modeling team. You will write production-grade code, collaborate on design reviews, and help advance ML-based advertising models at scale.

The role emphasizes building and deploying recommendation systems, end-to-end ML, and working closely with cross-functional teams to improve user experience and revenue. In-person interviews are part of the process, and equity/benefits accompany the attractive package.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience programming in Python or C++.
• 1 year of experience building and deploying recommendation systems models in production.
• 1 year of experience with end-to-end machine learning.

Responsibilities

• Write product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Design and optimize deep learning based ML models to predict users’ interaction with different ad formats across Google’s various ad delivery channels.

Skills

Python

C++

Recommendation systems

End-to-end ML

Education

Bachelor’s degree

Master’s degree or PhD

Job description

Google Mountain View, CA invites a Software Engineer III to join the App Ads Horizontal Modeling team. You will write production-grade code, collaborate on design reviews, and help advance ML-based advertising models at scale.

The role emphasizes building and deploying recommendation systems, end-to-end ML, and working closely with cross-functional teams to improve user experience and revenue. In-person interviews are part of the process, and equity/benefits accompany the attractive package.