Software Engineer III, AI/ML, Google Ads

1 Month ago • 3-5 Years • Artificial Intelligence

Job Summary

Job Description

This Software Engineer III role focuses on AI/ML within Google Ads' Privacy Centric Measurement team. Responsibilities include writing and reviewing code, contributing to documentation, debugging systems, and implementing ML solutions. The ideal candidate will have experience with ML infrastructure, model optimization, data processing, and at least one specialized ML area (e.g., speech/audio, reinforcement learning). The role involves collaborating with stakeholders and ensuring best practices in code quality and efficiency. The team's mission is to balance advertiser needs with user privacy in Google Ads, which encompasses search, display, shopping, travel, and video advertising.
Must have:
  • Bachelor's degree or equivalent experience
  • 2+ years software development experience
  • 2+ years experience with data structures/algorithms
  • 1+ year experience with ML infrastructure
  • Experience in at least one ML specialization
Good to have:
  • Master's or PhD in CS
  • Experience with accessible technologies

Job Details

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
  • 2 years of experience with data structures or algorithms.
  • 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  • 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

  • Master's degree or PhD in Computer Science, or a related technical field.
  • Experience developing accessible technologies.

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.

The Privacy Centric Measurement team's mission is to ensure that Google continues to serve the needs of our advertisers to understand their spend, while also maintaining a high level of privacy for our users.

Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.

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.
  • Implement solutions in one or more specialized Machine Learning (ML) areas, utilize ML infrastructure, and contribute to model optimization and data processing.

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