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ML Infrastructure Engineer in San Jose at PayPal

Date Posted: 5/9/2021

Job Snapshot

Job Description

Fueled by a fundamental belief that having access to financial services creates opportunity, PayPal (NASDAQ: PYPL) is committed to democratizing financial services and empowering people and businesses to join and thrive in the global economy. Our open digital payments platform gives PayPal’s 392 million active account holders the confidence to connect and transact in new and powerful ways, whether they are online, on a mobile device, in an app, or in person. Through a combination of technological innovation and strategic partnerships, PayPal creates better ways to manage and move money, and offers choice and flexibility when sending payments, paying or getting paid. Available in more than 200 markets around the world, the PayPal platform, including Braintree, Venmo and Xoom enables consumers and merchants to receive money in more than 100 currencies, withdraw funds in 56 currencies and hold balances in their PayPal accounts in 25 currencies.

Machine Learning Infrastructure Engineer to build scalable, highly available and robust platforms democratizing AI/ML for the company.


- Design, build, evolve, and scale state-of-the-art Machine Learning system infrastructure powering PayPal's AI/ML and Data Processing Platforms.
- Explore, evaluate and utilize cutting edge Machine Learning frameworks and solutions in the industry, iterate quickly in prototyping platform build-ups.
- Work with Product Owners, Architects, and platform users to design, implement and test customer facing Machine Learning platform capabilities.
- Work with Machine learning / Deep learning researchers and backend engineers to implement scalable solutions to solve complex problems.
- Drive platform user adoptions through documentation, presentations and demos.


- 2 years minimum experience in software development industry.
BS/MS in Computer Science or equivalent experience in related field.
- Solid software engineering skills with proficiency in one or more programming languages including Java, Python, Golang, Scala, Julia, etc.
- Experience in design and implement large scalable distributed systems with micro-services and heterogenous platform components.
- Experience with Machine Learning frameworks and libraries such as H2O, TensorFlow, PyTorch, SciKit-Learn, Keras, Spark MLlib, XGBoost, LightGBM etc. is a plus.
- Experience with data processing technologies (batch & streaming) and pipelines such as Spark, Flink, Google Dataflow, Dataproc etc. is a plus.
- Experience with leading industry Machine Learning tools and operation framework such as MLflow, Kubeflow, Airflow, Seldon Core, TFServing etc. is a plus.
- Experience in container-based deployment using Docker and Kubernetes.
- Experience in monitoring and performance analysis of Machine Learning AI and GPU server platforms using tech stacks and tools such as Splunk/SignalFX, ELK, Grafana, Prometheus etc. is a plus.
- Strong verbal and written communication skills.

We're a purpose-driven company whose beliefs are the foundation for how we conduct business every day. We hold ourselves to our One Team Behaviors which demand that we hold the highest ethical standards, to empower an open and diverse workplace, and strive to treat everyone who is touched by our business with dignity and respect. Our employees challenge the status quo, ask questions, and find solutions. We want to break down barriers to financial empowerment. Join us as we change the way the world defines financial freedom.

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at



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