Google

Senior Software Engineer, Map Ads Machine Learning

Google Mountain View, California, United States · $174K–$252K/yr

Software Development · 10,001+ employees

21 h ago
machine-learning Senior (5-10 yrs) Full-time United States
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About the role

Develop and maintain machine learning models to optimize ad retrieval, quality, and pricing. Collaborate with cross-functional teams to design, test, and deploy scalable software solutions while analyzing experiment results to improve ad performance.

What they look for

Python C++ Machine Learning Reinforcement Learning ML Infrastructure Model Deployment Model Evaluation Data Processing Software Architecture Ads Serving Data Structures Algorithms Technical Leadership Distributed Computing Information Retrieval

Requirements

Requires a bachelor's degree and at least 5 years of programming experience in Python or C++. Candidates must have 3 years of experience in machine learning, including model deployment and infrastructure, along with strong backend engineering skills.

Benefits

Bonus Equity Health Insurance

Full description

Minimum qualifications:

  • 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, 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:

  • 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 developing accessible technologies.
  • Experience with ads serving.

About the job:

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 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. You will also have the opportunity to contribute to the search renaissance with new integrations in AI Mode on Maps.

As a part of our team, you will be working on improving the pre-click and post-click quality of the ads. Your role requires prior experience working with ML models as well as strong backend engineering skills.

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

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

  • Write and test 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.).
  • Analyze experiment results and identify opportunities for improvements in ad quality, user happiness, and business.
  • 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.
  • Develop and work with ML models to improve the ads retrieval, pre/post click quality, pricing, etc.

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