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Staff Software Engineer, Private Machine Learning

GoogleMountain View, CA, USA

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience with machine learning recommendation systems in the context of Ads.
  • 3 years of experience with software design and architecture.
  • Experience with open source technologies.

Preferred qualifications:

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • 8 years of experience with data structures/algorithms.
  • 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  • 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
  • Experience in Privacy Preserving Machine Learning, Privacy Preserving System Design or Trusted Execution Environments.

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 join the team in the early stages with the opportunity to shape the future of private advertising, and you will have the opportunity to research, prototype, build, and ship innovative features for creating secure and private machine learning solutions for ads machine learning problems.

The Privacy Sandbox initiative aims to create technologies that both protect people's privacy online and give companies and developers tools to build thriving digital businesses. Our team is dedicated to strengthening the Web and Android platform against tracking and fingerprinting, while also developing new privacy-preserving APIs to support personalization and measurement on the web. We are committed to collaborating with stakeholders in the industry to develop and implement viable, alternative solutions in a way that protects the privacy of users while also ensuring the continued vitality of the web.

The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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.

Responsibilities

  • Research and understand different ML training, advertising use cases in the industry, design and implement ML simulations to represent those problems in our custom ML training setup.
  • Influence, coach and lead a team of distributed engineers to design experiments to understand eligible training techniques better, quantify model quality and run experiments in a reliable fashion.
  • Think about the impact of DP and confidential computing technologies like TEEs on the ML training characteristics and related costs. Think about open-source implementations of these solutions and platformize them for public usage.
  • Think about private solutions, relying on techniques like DP-SGD, to solve those ML optimization problems. Collaborate closely with Google research on shipping private modeling techniques for the ads ecosystem.
  • Design, develop, test, deploy, maintain, and enhance large scale software solutions.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

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