Job Description Summary: What you need to know about the role:
We are hiring talented and creative ML engineers for the AIML platform team based in Shanghai, China. You will be customer-centric, strategic & analytical in decision making and laser-focused on executing at scale. You thrive on the challenge of building and optimizing platforms at scale, are deeply passionate about leveraging cutting-edge technologies, and are dedicated to innovation and market success. You will have a chance to work on solving real-world problems and gain practical experience in the end-to-end Machine Learning life cycle. You will design, build, and optimize the platform for ML pipeline and data infrastructure. Additionally, you will gain domain expertise in a variety of industries, working with data scientists, researchers, and engineers to build ML models used across all PayPal domains.
Meet our Team: PayPal AI/ML Platform is responsible for building the ML platform to help data scientists with the end-to-end model development lifecycle. We build state-of-the-art and innovative ML infrastructure to support key product functions such as Fraud risk, Compliance, Personalization, Recommendations, Customer success, and other domains across PayPal.
Your way to impact: Strong critical thinking and problem-solving skills with the ability to address complex technical and non-technical challenges.Ability to influence at all levels of the organization and across multiple domains.Ability to lead complex technical and data science discussions and engagements that involve multiple personas including data scientists, data engineers, analysts, and developers.Your day-to-day: Design and develop highly scalable and efficient platform that enables data scientists to build, deploy, and monitor machine learning solutions end-to-end.Ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices.Drive innovation by researching and incorporating state-of-the-art machine learning techniques, tools, and frameworks into the platform.Effective communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner.Mentor team members, provide technical guidance, and foster a culture of collaboration, innovation, and continuous learning.Explore state-of-the-art deep learning techniques and partner with data science and domain engineering teams to support the business transformation through AI.Develop trusted partnerships with business, product, data scientists, and architecture leaders to drive optimized platform product delivery.What do you need to bring: Solid track record of over-achieving engineering and platform delivery and scaling targets in high-volume, innovative, and fast-paced high-pressure environments; proven results in delivery on platform products.Masters/bachelor's in computer science, Computer engineering, Machine Learning, Data Mining, Information Systems, or related disciplines, with technical expertise in one or more of the above-mentioned areas or equivalent practical experience.3+ year experience for MS; 5+ year experience for BS.Strong proficiency in machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models.Expertise in programming languages such as Python, Go, Java, and proficiency in machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc.Stay up-to-date with the latest advancements in AI/ML technology and industry trends, and leverage this knowledge to enhance the platform's capabilities.Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).Strong communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner.Demonstrated leadership abilities, including the ability to inspire, mentor, and empower team members to achieve their full potential.Experience with Jupyter Notebook, Kubeflow, Airflow, Argo, GPU, and HPC.Experience building ML infrastructure or MLOps platforms and Big Data platforms technologies such as Hadoop, BigQuery, Spark, Hive, and HDFS.Additional Job Description: Subsidiary: PayPal
Travel Percent: 0
For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.
Our Benefits: At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset—you. That's why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.
We have great benefits including a flexible work environment, employee shares options, health and life insurance, and more. To learn more about our benefits please visit paypalbenefits.com.
Who We Are: Click Here to learn more about our culture and community.
Commitment to Diversity and Inclusion: 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 ******.
Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.
We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.
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