Sr Machine Learning Engineer

PayPal • San Jose, CA

1d • Hybrid

About The Position

As a senior Machine Learning Engineer in PayPal’s Risk Data Science organization, you will play a critical role in advancing the company’s fraud detection capabilities through cutting-edge machine learning research and scalable automation. Our team develops state-of-the-art AI solutions that protect millions of users globally from fraudulent activities, while enabling seamless payment experiences. You will work at the forefront of ML innovation, leveraging PayPal’s vast and rich datasets to design, build, and deploy high-impact models across the fraud prevention landscape. From deep learning and graph-based modeling to reinforcement learning and risk foundation models, you’ll have the opportunity to apply advanced techniques to real-world challenges with immediate business relevance.

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.

Nice To Haves

• Research experience in ML/AI areas with publications or open-source contributions a plus
• Experience with transformer-based architectures (e.g., BERT, GPT, T5), including fine-tuning and domain adaptation
• Knowledge of reinforcement learning, including policy optimization, value function approximation, or bandit algorithms
• Hands-on experience with graph-based models (e.g., GCN, GraphSAGE, GAT) or graph representation learning
• Experience with AI or agentic systems, including exposure to LLM-based agents, autonomous decision-making components, or multi-agent workflows; ability to integrate or operationalize these capabilities within data or ML solutions.
• Familiarity with LLM post-training techniques, such as RLHF, reward modeling, or alignment tuning
• Experience with semi-supervised, self-supervised, or unsupervised representation learning
• Knowledge of causal inference, anomaly detection, and incremental/continual learning
• Exposure to synthetic data generation techniques for model training or evaluation
• Prior work in fraud detection, risk modeling, or other high-impact, high-noise domains

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.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees