Senior Software Engineer, Map Ads Machine Learning

Senior Software Engineer, Map Ads Machine Learning

Google – Mountain View, CA, USA

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience programming in Python or C++.
• 3 years of experience with one or more of the following: reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 3 years of experience with end‑to‑end Machine Learning (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.

• Master’s degree or PhD in Computer Science or a related technical field.
• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.
• Experience with ads serving.

In this role, you will work on exciting issues in ads serving, quality, and formats to enhance user and advertiser value. You will have the opportunity to shape a fast‑growing ads product and contribute to the search renaissance with new integrations in AI Mode on Maps. You will work on improving the pre‑click and post‑click quality of ads, requiring prior experience with ML models and strong backend engineering skills.

• Write and test product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices for style guidelines, code quality, testability, and efficiency.
• Analyze experiment results and identify opportunities for improvements in ad quality, user satisfaction, and business impact.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and their impact on hardware, network, or service operations and quality.
• Develop and work with ML models to improve ads retrieval, pre/post‑click quality, pricing, and related processes.

US: $174,000 – $253,000 (USD) + 15% bonus target + equity + benefits.

Individual pay is determined by factors including job‑related skills, experience, and relevant education or training.

Learn more about benefits at Google.

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See also Google’s EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

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