Staff Machine Learning Engineer

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities.

Job Summary: Summary Join the Global Fraud Prevention team to build the data infrastructure, automation, and machine learning capabilities that power risk decisioning at global scale. As a Staff Machine Learning Engineer, you will design and deliver data-driven initiatives, production ML pipelines, and data products that improve fraud detection and prevention. You will apply advanced analytics, statistical modeling, and machine learning to transform complex data into actionable insights, while ensuring data quality, governance, and operational excellence. Partnering with Product, Engineering, Risk, and Analytics teams, you will deploy data-driven solutions that reduce fraud losses and enhance customer experience. You will also mentor engineers and drive adoption of modern AI-assisted development tools. The ideal candidate has extensive experience with large-scale data platforms, Python, SQL, cloud technologies, and machine learning for risk or fraud solutions.

Job Description: Essential Responsibilities:

• Lead the development and optimization of advanced machine learning models.
• Oversee the preprocessing and analysis of large datasets.
• Deploy and maintain ML solutions in production environments.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models, making necessary adjustments.

Minimum Qualifications:

• 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
• Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Additional Responsibilities & Preferred Qualifications: Additional Responsibilities

• Partner with Product and Platform Engineering teams to build scalable, secure, and innovative machine learning-powered data products, and large-scale data processing solutions that improve customer experiences and business outcomes.
• Collaborate closely with Data Engineering, Analytics, and Platform teams to ensure high-quality datasets, reliable feature pipelines, and robust monitoring infrastructure.
• Design, build, and manage robust data pipelines and data products that transform complex, multi-source datasets into actionable business insights.
• Oversee data ingestion, preprocessing, transformation, feature engineering, and analysis of large-scale structured and unstructured datasets.
• Leverage large-scale datasets to perform exploratory analysis, feature engineering, anomaly detection, and pattern discovery to identify emerging fraud threats and business opportunities.
• Develop and optimize risk rules, and mitigation strategies using advanced analytics, machine learning, experimentation techniques.
• Drive best practices in modern data architecture, data engineering, streaming and batch processing, and scalable design for high-volume transaction environments.
• Communicate analytical findings, technical recommendations, and business impact effectively to stakeholders, executives, and senior leadership.
• Lead, mentor, and develop high-performing teams of Data Scientists, Machine Learning Engineers, and Data Engineers while fostering innovation and technical growth.

Preferred Qualifications

• 6+ years of experience in Data Engineering, Data Science, Machine Learning Engineering, Fraud Analytics, Risk Modeling, or related disciplines.
• Experience designing and deploying AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, and intelligent automation workflows
• Familiarity with Agentic AI frameworks and orchestration platforms such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, OpenAI Agents SDK, or similar technologies.
• Strong experience designing and supporting large-scale data platforms, distributed systems, and production-grade data pipelines.

Subsidiary: PayPal

Travel Percent: 0 PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact\-us. 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 comprehensive, choice-based programs, to support all aspects of personal wellbeing—physical, emotional, and financial—delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.

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 paypalglobaltalentacquisition@paypal.com.

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. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.