Staff Software Engineer, Payments Risk, ML Infrastructure

Minimum qualifications:

• Bachelor's degree in Computer Science or related technical field, or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products.
• 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
• Experience building machine learning solutions and leveraging specific machine learning architectures.
• Experience in the Java programming language.

Preferred qualifications:

• 8 years of experience with data structures/algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• Experience with Java (primary language), in addition to C++, Python or Kotlin.
• Experience with distributed computing, systems and data concepts.
• Experience in one of the following areas: internet technology, online search, E-Commerce, online payments or online advertising/publishing, policy enforcement/user trust/risk/fraud investigation or product abuse.

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.

Our mission is to make payments easy for good users and hard for fraudsters.This is a huge area of opportunity as we protect business for Google each year. Fraudsters are constantly evolving their tactics, and Google is constantly launching new products, so we continuously need to make our systems more sophisticated and extensible. The team is responsible for protecting Google's customers and businesses from payment fraud, including; stolen credit cards, Refund abuse, Account hijacking, Banking manipulation, and many other attack vectors.

In this role, you can both contribute as a Machine Learning (ML) software engineer in improving model performance and you will have to possess an excellent infrastructure and ML signal serving background.

Whether it is paying online with Autofill, using tap and pay in stores, or using the Google Pay app, the Payments team at Google is focused on making payments simple, seamless, and secure. In addition to consumer payment technologies, the Payments team also powers the money movement between Google and its consumers and businesses.

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

• Manage the tradeoff between catching fraud and maintaining a good user experience.
• Maintain small degradations or outages that could result in large business impacts to Google.
• Identify new fraud patterns and improve the team's ability to identify and incorporate new signals as fraud continues to evolve.
• Collaborate closely with model owners and have a large impact on the construction and serving of all features into the team's ML models.
• Design and build critical metrics needed by the business to better understand fraud prevention and potential impact to customers/users.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .