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Anti Fraud - Machine Learning Engineer

Company: Zoom
Location: san jose
Posted on: May 3, 2021

Job Description:

Zoomies help the world connect - and deliver happiness while doing it. We set out to build the best video conferencing product for the enterprise, and today help people communicate better with products like Zoom Phone, Zoom Rooms, Zoom Video Webinars, Zoom Apps, and OnZoom.

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

Zoom is an award-winning workplace. We have been recognized by Comparably as #1 CEO, Company Happiness, Benefits, Compensation, Diversity, and more! Not to mention we've been awarded by Glassdoor as the 2nd Best US workplace & Best Large Company US CEO in 2018, Wealthfront, and Business Insider. Our culture focuses on delivering happiness, our commitment to transparency, and the tangible benefits we provide our employees and our customers.

What you'll do:

* Teamwork with different function team to design abuse, porn, tele-fraud detection model base on different business product requirement and protection policy. * Responsible for developing telephone anti-fraud, anti-spam, anti-pornography, anti-abuse registration and other services * Responsible for the implementation and practice of related algorithms under the current mainstream stream computing platform


* Collaborate with cross-functional teams to develop AI-based solutions to prevent unwanted abuse of Zoom services, including Zoom Phone, Zoom Meetings, OnZoom, and other future products * Extract and process real-time and batch data from Zoom services for data exploration, aggregation, and validation * Research, experiment, and evaluate statistical and machine learning techniques to develop fraud detection systems that satisfy business requirements and security policies * Train, evaluate, and validate fraud detection models using mainstream cloud computing platforms * Serve trained fraud detection models as prediction services into the production environment for on-line (streaming) and off-line (batch) inferences * Follow MLOps best practices to develop and maintain machine learning pipelines that can automate the retraining and deployment of new fraud detection models

Job Requirements:

* Minimum Qualifications: * Does not require sponsorship * MS or PhD in Computer Science, Engineering, Statistics, or similar fields with at least 3 years of working experience with production-scale ML systems * Advanced proficiency in Java or Python * Proven experience with common ML libraries, such as Scikit-learn, TensorFlow, PyTorch, Keras * Strong fundamentals in statistics and machine learning * Knowledge of and experienced with cloud computing and big data frameworks, such as AWS, GCP, Spark, Flink, or Beam * Proficient in standard software development, such as version control, debugging, testing, and deployment * Ability to use MLOps frameworks such as TensorFlow Extended, Kubeflow, or MLFlow * Demonstrated problem-solving mindset with analytical skills and attention to detail

* Preferred Qualifications: * MS or PhD in Computer Science, Engineering, Statistics, or similar fields with at least 3 years of working experience with production-scale ML systems * A track record in conceptualizing and building end-to-end big data frameworks * Peer-reviewed publications in conferences or journals * Experience in enterprise fraud prevention or telecommunications risk management * Language: English, Mandarin is a plus

Explore Zoom:

* Hear from our leadership team

* Browse Awards and Employee Reviews on Comparably

* Visit our Blog

* Zoom with us!

* Find us on social at the links below and on Instagram

Keywords: Zoom, San Jose , Anti Fraud - Machine Learning Engineer, Other , san jose, California

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