Senior Staff Machine Learning Engineer

Experteer Overview In this role you will define the strategic vision for embedding machine learning across PayPal’s software ecosystem, shaping scalable ML-powered features. You will collaborate with engineering and data science teams to build, optimize, and deploy models that meet performance and reliability targets. You will lead production ML initiatives, monitor models in production, and design data pipelines and testing to ensure rapid, high-quality delivery. This is a chance to influence risk-aware, data-driven payments tech at a global scale and contribute to PayPal’s mission of inclusive financial services. Compensation / Benefits * Define and drive the ML strategy within the software ecosystem * Analyze product architecture to design ML models using algorithmic programming, data management, and data visualization techniques * Collaborate with Engineering and Data Science teams to deliver scalable features * Lead ML model optimization for integration into products and services * Monitor deployed models and iterate as needed for performance * Organize large datasets and manage cloud-based data processing and deployment * Create and implement analytics pipelines and deploy ML solutions in production * Define testing sequences for ML components and implement automated CI/CD-ready code Tasks * Bachelor’s degree in Computer Science, Data Science, Information Systems, or related field plus 8 years of experience * Experience developing end-to-end ML models * Experience managing externally facing ML models * Experience with ML tooling and feature assessment * Proficiency in Python and SQL (8 years) * Experience with credit and fraud risk models * Experience with distributed computing (Spark) * Banking/fintech experience and model risk management knowledge * Cloud platform experience (AWS, Azure, or GCP) with 8 years * Tools for data processing and model deployment (8 years) * Experience leading ML model design, implementation, deployment (6 years) * CI/CD pipelines (6 years) * Proficiency with PyTorch, TensorFlow, XGBoost, Scikit-learn (6 years) * AWS SageMaker (6 years) * Natural Language Processing (8 years) * Statistical models (8 years) * Agile methodology (5 years) * Artificial neural networks (8 years) Key requirements * hybrid work model * generous paid time off * healthcare coverage * financial wellbeing resources * equity or incentive compensation where applicable * career development opportunities

• Monitor deployed models and iterate as needed for performance * Organize large datasets and manage cloud-based data processing and deployment * Create and implement analytics pipelines and deploy ML solutions in production * Define testing sequences for ML components and implement automated CI/CD-ready code Tasks * Bachelor’s degree in Computer Science, Data Science, Information Systems, or related field plus 8 years of experience * Experience developing end-to-end ML models * Experience managing externally facing ML models * Experience with ML tooling and feature assessment * Proficiency in Python and SQL (8 years) * Experience with credit and fraud risk models * Experience with distributed computing (Spark) * Banking/fintech experience and model risk management knowledge * Cloud platform experience (AWS, Azure, or GCP) with 8 years * Tools for data processing and model deployment (8 years) * Experience leading ML model design, implementation, deployment (6 years) * CI/CD aaaaa with (6 years) * Proficiency with PyTorch, TensorFlow, XGBoost, Scikit-learn (6 years) * AWS SageMaker (6 years) * Natural Language Processing (8 years) * Statistical models (8 years) * Agile methodology (5 years) * Artificial neural networks (8 years) Key requirements * hybrid work model * generous paid time off * healthcare coverage * financial wellbeing resources * equity or incentive compensation where applicable * career development opportunities