Staff Machine Learning Engineer — Agentic Systems

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:

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.

• Define the technical strategy and architecture for agentic systems supporting risk management products and platforms.
• Design and scale agent runtimes/orchestration: tool routing, planners, memory/state, long-running tasks, retries/fallbacks, and policy enforcement.
• Lead development of traditional AI/ML systems at scale for risk management, including data pipelines, feature stores, training/serving, and monitoring.
• Drive neural network and deep learning adoption where it provides lift (e.g., transformers, embeddings, representation learning, sequence modeling) and guide architecture, training, and optimization decisions.
• Drive algorithmic choices and improvements across both agentic and classical approaches: retrieval/reranking, planning methods, ranking/optimization, uncertainty estimation, and robust decisioning.
• Build enterprise-grade evaluation and governance: golden datasets, scenario libraries, automated regression, and continuous monitoring.
• Establish guardrails: tool permissions, traceability patterns, approval workflows, and human-in-the-loop controls for risk use cases.
• Provide technical leadership across data engineering and ML: data contracts, scalable feature pipelines, data quality/lineage, and efficient retrieval systems.
• Define and standardize ML pipelines across teams, including training/inference workflows, reproducibility, model registry practices, and CI/CD for ML.
• Optimize system performance end-to-end (quality/latency/cost): caching, batching, distillation, model selection, and systems tuning.
• Mentor engineers, lead design reviews, and set standards for ML/agent quality, testing, and production readiness.
• Partner cross-functionally to ensure solutions are measurable, reliable, and aligned to risk strategy and business goals.

• Demonstrated ownership of complex, high-reliability ML systems in production, including architecture and operational excellence.
• Proven experience developing and operating large-scale agentic systems in production (multi-step workflows, tool use, RAG, safety, observability).
• Deep expertise in traditional AI/ML algorithms with applied experience (e.g., learning-to-rank, anomaly detection, time series, NLP, deep learning, optimization, probabilistic modeling, RL) and strong fundamentals in statistics and experimentation.
• Significant hands-on experience with neural networks (e.g., training/fine-tuning in PyTorch/TensorFlow; transformers/embeddings; model optimization and deployment).
• Strong data engineering depth (e.g., distributed data processing, ETL design, data modeling, feature store patterns, quality/lineage).
• Strong software engineering and distributed systems skills (Python; service design; event-driven systems; concurrency; data pipelines).
• Track record of leading cross-functional initiatives and influencing technical direction across multiple teams.
• Strong business acumen: ability to define success metrics, reason about trade-offs (loss, approvals, friction, cost), and align technical roadmaps to business goals.

• Demonstrated experience delivering AI/ML solutions for risk management domains (e.g., fraud, transaction risk, credit risk, AML, disputes/chargebacks) or analogous decisioning systems.
• Experience with multi-agent coordination patterns, policy engines, or workflow automation platforms.
• Advanced measurement practices (A/B testing, causal inference, counterfactual evaluation).
• Publications, patents, open-source leadership, or recognized thought leadership in applied AI/ML.

Subsidiary:

Travel Percent:

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 [email protected].  

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.