Anti-Fraud Machine Learning Engineer

Engineering (EN)

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Anti-Fraud Machine Learning Engineer

  • R9573
  • Bay Area, California, United States
  • Engineering (EN)
  • Full time

Work Styles at Zoom

In most cases, you will have the opportunity to choose your preferred working location from the following options when you join Zoom: in-person, hybrid or remote. Visit this page for more information about Zoom's Workstyles.

About Us

Zoomies help people stay connected so they can get more done together. We set out to build the best video product for the enterprise, and today help people communicate better with products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinars.

We’re problem-solvers, working at a fast pace to design solutions with our customers and users in mind. Here, you’ll work across teams to deliver impactful projects that are changing the way people communicate and enjoy opportunities to advance your career in a diverse, inclusive environment.

Position Summary

As Zoom grows and expands our product reach, fraudulent activities become more common and fraudsters become more sophisticated. In order to stay ahead and catch fraud as close as possible to the fraud event and leverage predictive techniques to anticipate and identify fraud events ASAP, we need to leverage Machine Learning and more complex algorithms in addition to traditional data analysis. This role will help us catch more fraud events, save wasted dollars, and improve Zoom’s customer experience.

Responsibilities

  • Improve our fraud detection on all Zoom’s products (Zoom Phone, Zoom Meeting Audio conference) by leveraging known fraud characteristics and leveraging classification algorithms to identify fraud signals, catch, stop, and even prevent fraud

  • Drive reduction of fraud dollars measurable percentage in all Zoom’s products

  • Work with CSM/Trust & Safety/NOCs/PMs to identify known characteristics of fraudulent activity in Zoom’s Phone, Meeting audio conference side.

  • Implement highly optimized fraud detectors using best-in-breed ML and Big Data technologies, as well as leveraging traditional data analytics techniques

Qualifications

  • 5+ years of experience using SQL and Python for data manipulation

  • Demonstrated problem-solving mindset with analytical skills and attention to detail

  • Practical experience with common ML libraries, such as Scikit-learn, TensorFlow, PyTorch, or Keras

  • Strong fundamentals in machine learning theories

  • Ability and willingness to be on-call in some weekends and holidays (taking turns with the rest of the team) to support Fraud systems

Preferred Qualifications

  • Knowledge of MLOps frameworks such as TensorFlow Extended, Kubeflow, or MLFlow

  • Proficient in leveraging Spark or Flink to create and manipulate data pipelines in an AWS big data environment

We believe that the unique contributions of all Zoomies is the driver of our success. To make sure that our products and culture continue to incorporate everyone's perspectives and experience we never discriminate on the basis of race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. Zoom is proud to be an equal opportunity workplace and is an affirmative action employer. All your information will be kept confidential according to EEO guidelines. 

We welcome people of different backgrounds, experiences, abilities and perspectives including qualified applicants with arrest and conviction records and any qualified applicants requiring reasonable accommodations in accordance with the law. If you need any assistance or accommodations due to a medical condition, or if you need assistance accessing our website or completing the application process, please let us know by emailing us at careers@zoom.us.

Zoom requires all U.S. employees who will work in person at a Zoom office, attend in-person Zoom meetings or have in-person customer meetings to be fully vaccinated.  Zoom will consider requests for reasonable accommodations for religious or medical reasons as required under applicable law.

At Zoom, we care about our employees, their families, and their well-being. As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways. To view our benefits, click here.

Explore Zoom:

#LI-Remote

Fraudulent Employment Offers

Zoom is aware of scams that involve fake Zoom job listings posted on third-party sites. Responding applicants are contacted primarily over email, InMail and/or chat applications by people impersonating Zoom employees. Eventually a fake offer letter is sent in exchange for personal identification information as part of a fake new-hire screening process.

Please be advised that these offers, communications and impersonations are illegitimate and fraudulent. All communication with Zoom employees come from a “@zoom.us” email address. Zoom job applicants complete an interview process including in-person (on Zoom) meetings and phone calls. Our process also requires you to create an account with our applicant tracking system, Workday.

Zoom will never ask for your personally identifying information during the interview process or ask you to pay money or purchase equipment. If you have received a message from Zoom that appears suspicious, please contact careers@zoom.us. 

 

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