Job Details
Posted date: Sep 05, 2024
There have been 2 jobs posted with the title of Staff Privacy Engineer, AI/ML, Devices and Services all time at Google.There have been 2 Staff Privacy Engineer, AI/ML, Devices and Services jobs posted in the last month.
Location: Kirkland, WA
Level: Director
Estimated salary: $236,500
Range: $189,000 - $284,000
Description
Lead the development and execution of technical privacy strategies and adoption of Privacy Enhancing Technology for AI and ML projects. Identify, assess, and develop mitigation strategies for privacy risks related to AI and ML features, models, and datasets. Guide and mentor team members and product leads on best practices in AI/ML privacy, cultivate relationships with partner teams to align priorities and technical contributions to support product teams. Provide knowledge in AI and Generative AI privacy risks and mitigation including privacy preserving techniques (e.g., differential privacy, federated learning). Develop and maintain privacy standards and frameworks that align with laws and regulations, external commitments, and customer expectations.The Devices and Services Privacy team operates security, privacy, and safety programs to protect users, improve the security and privacy of Google devices (and related apps and services), and ensure users are confident that Google products are safe and trustworthy.
As a Staff Privacy Engineer, you will help drive privacy solutions into all products that fall under the Devices and Services portfolio. You will also work across product areas to manage privacy and data risks.
The US base salary range for this full-time position is $189,000-$284,000 + 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 benefits at Google.
Qualifications
Minimum qualifications: Bachelor's degree or equivalent practical experience.7 years of experience working in a privacy related field (e.g., security engineering, data engineering, data scientist, compliance engineering etc.).
2 years of experience driving initiatives and solutions for technological problems with company-wide impact, that maintain or elevate the privacy posture of the organization, and influencing executive decisions.
2 years of experience determining privacy technologies/frameworks to solve technical and operational problems, and customizing existing solutions and frameworks to support business objectives.
Experience in ML privacy-preserving techniques (e.g., differential privacy, federated learning) and assessing ML risks.
Preferred qualifications: 3 years of experience leading the application of privacy technologies (e.g., differential privacy, automated access management solutions, etc.) to solve technical and data management problems, customizing existing solutions and frameworks to meet user needs.
Experience in the development of ML models and applications. Knowledge of regulatory frameworks (e.g., GDPR, CCPA) and experience working with regulators or regulatory authorities. Knowledge of privacy principles, with a passion for keeping users and their data safe.
Extended Qualifications
Bachelor's degree or equivalent practical experience.7 years of experience working in a privacy related field (e.g., security engineering, data engineering, data scientist, compliance engineering etc.).
2 years of experience driving initiatives and solutions for technological problems with company-wide impact, that maintain or elevate the privacy posture of the organization, and influencing executive decisions.
2 years of experience determining privacy technologies/frameworks to solve technical and operational problems, and customizing existing solutions and frameworks to support business objectives.
Experience in ML privacy-preserving techniques (e.g., differential privacy, federated learning) and assessing ML risks.
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