Sr Machine Learning Engineer

PayPal•San Jose, CA

4d•$169,262 - $243,500•Hybrid

About The Position

PayPal, Inc. seeks Sr Machine Learning Engineer in San Jose, CA. This role involves conducting cutting-edge research in machine learning to develop solutions for complex business challenges, with a primary focus on payment fraud detection. The engineer will analyze large, complex datasets to extract actionable insights, design, develop, and deploy scalable machine learning algorithms, and integrate them into PayPal’s AI/ML systems. Experimentation with innovative models and new approaches to enhance fraud detection capabilities is key. Collaboration with cross-functional and international teams is essential to align technical solutions and contribute to the development of state-of-the-art technologies, ultimately advancing AI/ML technologies to maintain PayPal’s leadership in financial technology. Partial telecommuting is permitted from within a commutable distance.

Requirements

Doctorate degree, or foreign equivalent, in Computer Science, Computer Engineering, or a closely related field plus at least one year of experience in the job offered or a related occupation.
OR Master’s degree, or foreign equivalent, in Computer Science, Computer Engineering, or a closely related field plus four years of experience in the job offered or a related occupation.
Machine learning frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn, used for model development and experimentation (1 year)
Machine learning workflow management and experiment-tracking tools (1 year)
Computer science fundamentals, data structures, and algorithms (1 year)
Object-oriented design methodology and application development in Python (1 year)
Graph-based machine learning, graph neural networks, and graph data modeling and analysis (1 year)
Research methodology, documentation, and scientific communication in applied machine learning (1 year)
Algorithm optimization, computational efficiency, and system-level integration for scalable machine learning research (1 year)
Mathematical and theoretical foundations of machine learning, including calculus, linear algebra, matrix theory, information theory, optimization, and network science (1 year)
Cloud computing and high-performance computing for machine learning model training and experimentation (1 year)
Model interpretability and performance analysis for evaluating algorithmic reliability and improving model performance (1 year)
Experience designing, developing, and improving machine learning models for predictive modeling, unsupervised and self-supervised learning, pattern recognition, and representation learning (1 year)
Experience conducting applied machine learning research, including formulating modeling objectives, designing and implementing algorithms, conducting experiments and evaluating results, and iteratively refining models for performance improvement (1 year)
Experience implementing and enhancing graph-based and relational machine learning techniques for structured or graph data (1 year)
Experience performing data preprocessing, feature engineering, and statistical validation using Python to improve model robustness and generalization (1 year)
Experience designing and managing structured model-training workflows, including performance tuning, retraining, and experiment management for reproducible results (1 year)
Experience developing research prototypes, conducting ablation and sensitivity studies, and documenting results to support continuous model improvement (1 year)

Responsibilities

Conduct cutting-edge research in machine learning to develop solutions that address complex business challenges, focusing on payment fraud detection.
Analyze large, complex data sets to extract actionable insights that inform business strategies and decision-making.
Design, develop, and deploy scalable machine learning algorithms, integrating them into PayPal’s AI/ML systems.
Experiment with innovative models and new approaches to enhance fraud detection capabilities.
Collaborate with cross-functional and international teams to align technical solutions and contribute to the development of state-of-the-art technologies.
Contribute to the advancement of AI/ML technologies that help maintain PayPal’s leadership in financial technology.