Privacy Engineer III, Google Ads

5 Months ago • 2-4 Years • Artificial Intelligence • $136,000 PA - $200,000 PA

Job Summary

Job Description

As a Privacy Engineer III at Google Ads, you will be responsible for guiding engineering teams during product development to ensure that their data collection and usage practices are transparent, protect user privacy, and mitigate risk. You will conduct technical and policy reviews to identify and escalate potential privacy concerns. You will also lead and manage the development of new privacy features and tools in the machine learning space. You will provide privacy subject matter knowledge for machine learning and AI related reviews and contribute to product/business strategy, public policy, and legal initiatives to address and mitigate privacy risks.
Must have:
  • Bachelor's degree or equivalent practical experience
  • 2 years of experience designing solutions that maintain or enhance the privacy posture of the organization
  • 2 years of experience applying privacy technologies
  • Experience in machine learning, generative AI, or similar fields
Good to have:
  • Experience balancing risks in ambiguous situations with multiple stakeholders
  • Experience managing multiple requests, while determining resource allocation
  • Knowledge of common regulatory frameworks (e.g., GDPR, CCPA)
  • Knowledge of the Ads or online commerce domain
  • Excellent written and verbal communication, and presentation skills
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details


Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 2 years of experience designing solutions that maintain or enhance the privacy posture of the organization by analyzing and assessing proposed engineering designs (e.g., product features, infrastructure systems) and influencing stakeholders.
  • 2 years of experience applying privacy technologies (e.g., differential privacy, automated access management solutions, etc.), and customizing existing solutions and frameworks to meet organizational needs.
  • Experience in machine learning, generative AI, or similar fields.

Preferred qualifications:

  • Experience balancing risks in ambiguous situations with multiple stakeholders.
  • Experience managing multiple requests, while determining resource allocation (e.g., time, prioritization) to solve problems in a fast-paced, changing organization.
  • Knowledge of common regulatory frameworks (e.g., GDPR, CCPA).
  • Knowledge of the Ads or online commerce domain.
  • Excellent written and verbal communication, and presentation skills, with the ability to translate technical concepts to non-technical audiences.

About the job

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.

The US base salary range for this full-time position is $136,000-$200,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .

Responsibilities

  • Guide Engineering teams during product development to ensure that their data collection and usage practices are transparent, protect user privacy, and mitigate risk.
  • Conduct technical and policy reviews to identify and escalate potential privacy concerns.
  • Lead and manage development of new privacy features and tools in the machine learning space.
  • Provide privacy subject matter knowledge for machine language and AI related reviews.
  • Contribute to product/business strategy, public policy, and legal initiatives to address and mitigate privacy risks.

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