Own end-to-end development of agentic systems: planning, task decomposition, tool/function calling, state/memory, multi-step execution, and reliability patterns (fallbacks, retries, idempotency).
Build and maintain ML pipelines for training, validation, and inference, including feature generation, reproducible experiments, and automated deployment workflows.
Implement RAG and grounding pipelines to improve accuracy and auditability (retrieval, reranking, citations/traceability, context controls).
Establish evaluation systems: offline datasets, regression suites, online monitoring, drift detection, and error analysis for both agents and models.
Define and implement guardrails for agent actions: tool permissions, safe completion rules, policy constraints, and human-in-the-loop patterns where needed.
Contribute to data engineering needs: data contracts, scalable pipelines, feature generation, and data quality/lineage checks.
Improve runtime performance and operability: latency/cost optimization, observability (metrics/logs/traces), incident response and postmortems.
Requirements
3+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience.
Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
Several years of experience in designing, implementing, and deploying machine learning models.
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:
We're hiring a Senior Machine Learning Engineer to build and scale agentic AI systems for risk management in fintech. You will own end-to-end delivery of production-grade agents and ML models, improving decision quality, operational efficiency, and system reliability. This role requires strong depth across agentic systems and classical AI/ML, with the ability to lead projects and drive technical decisions.
Job Description:
Essential Responsibilities:
Develop and optimize machine learning models for various applications.
Preprocess and analyze large datasets to extract meaningful insights.
Deploy ML solutions into production environments using appropriate tools and frameworks.
Collaborate with cross-functional teams to integrate ML models into products and services.
Monitor and evaluate the performance of deployed models.
Paypal · Central Singapore, Singapore