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# Machine Learning Engineer

- **Company:** PayPal
- **Location:** San Jose, CA, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Artificial Neural Networks, Bash Shell, Big Data, Data Visualization, Database Queries, Apache Hive, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Unix Commands, Jupyter Notebook, Feature Engineering, Pytorch, Git, Google Bigquery, Text Analysis
- **Published:** August 11, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/machine-learning-engineer-san-jose-ca-usa-58894729

## About the Role

to fraud, and repayment behavior for merchant loans; run experiments to improve model performance * Ensure models solve business problems, comply with regulations, and enhance risk controls and operations Tasks * Master's degree in Mathematics, Statistics, or closely related field * Proficiency in Python (NumPy, PyTorch) * SQL proficiency in Google BigQuery or HiveQL * Experience with CNNs, RNNs, Transformers * NLP techniques for text analytics * Experimental design for model building and selection * Statistical analysis (regression, hypothesis testing) * Data visualization in Python or Excel * Unix command line and Bash scripting * Git for version control * Jupyter Notebooks and/or Google Colab for interactive analysis Key requirements * generous paid time off * healthcare coverage for you and your family * resources to create financial security * flexible hybrid work model (3 days in office / 2 days remote)

## Description

Experteer Overview In this role you will design and deployed predictive ML models to support credit, fraud, and repayment analytics for merchant loans. You will work with large datasets and collaborate with ML colleagues to implement advanced techniques that solve business problems. You will communicate insights through visualizations for stakeholders and help ensure model compliance and operational efficiency. The position offers a hybrid work model and opportunities to impact risk management and user experience at scale. Compensation / Benefits * Design, develop, implement, deploy, and monitor predictive models using ML techniques (neural networks, tree-based models) * Work with large volumes of data; extract insights and perform feature engineering * Collaborate with ML scientists and engineers to experiment and deploy advanced ML solutions * Communicate complex analysis and modeling results through visualizations for diverse stakeholders * Build credit models to predict delinquency, fraud, and repayment behavior for merchant loans; run experiments to improve model performance * Ensure models solve business problems, comply with regulations, and enhance risk controls and operations Tasks * Master's degree in Mathematics, Statistics, or closely related field * Proficiency in Python (NumPy, PyTorch) * SQL proficiency in Google BigQuery or HiveQL * Experience with CNNs, RNNs, Transformers * NLP techniques for text analytics * Experimental design for model building and selection * Statistical analysis (regression, hypothesis testing) * Data visualization in Python or Excel * Unix command line and Bash scripting * Git for version control * Jupyter Notebooks and/or Google Colab for interactive analysis Key requirements * generous paid time off * healthcare coverage for you and your family * resources to create financial security * flexible hybrid work model (3 days in office / 2 days remote)


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