1 day ago
San Jose, CA, USAStaff+
Base Salary
$228k - $301k/yr
Responsibilities
- Design and deploy scalable risk analytics and generative AI solutions and productize machine learning models.
- Develop AI agents that automate workflows, detect live issues, and provide fix suggestions.
- Lead architecture design, technical decision-making, and delivery across cross-functional and matrixed teams.
- Define technical standards and maintain code quality, performance, and reliability through testing, code reviews, and software engineering best practices.
- Research and incorporate state-of-the-art machine learning techniques, tools, and frameworks.
- Mentor senior and junior team members and provide technical guidance and strategic direction.
Requirements
- Master’s degree or foreign equivalent in Computer Science, Engineering, or a closely related field plus five years of experience, or a bachelor’s degree or foreign equivalent plus eight years of progressively responsible experience.
- Four years of experience designing and deploying production machine learning models and pipelines using Python and Java.
- Two years of experience developing and productizing generative AI solutions involving LLMs, RAG pipelines, or AI agents.
- Three years of experience with big data and distributed computing technologies such as Spark, Hadoop, or Flink.
- Four years of experience developing large-scale software applications using object-oriented design in Java or Python.
- Two years of experience deploying and managing ML/AI workloads on AWS, GCP, or Azure using Docker and Kubernetes.
- Two years of experience building data pipelines and ML feature engineering systems with Airflow, MLflow, or similar MLOps platforms.
- Two years of experience in risk analytics or fraud detection, including anomaly detection, payment risk, or transaction monitoring.
- One year of experience developing AI agents or workflow automation systems for issue detection, root cause analysis, or automated remediation.
- Four years of experience with code reviews, unit and integration testing, CI/CD pipelines, and version control such as Git.
- Three years of experience leading cross-functional data scientists, product managers, and system engineers in a matrix organization.
Benefits
- Partial telecommuting is permitted from a commutable distance, and PayPal’s balanced hybrid model generally provides three days in the office and two days at the office or home workspace.
- The role is based in San Jose, California, with a Monday-Friday, 9:00 a.m.-5:00 p.m. schedule and 40 hours per week.
- Benefits include paid time off, healthcare coverage for employees and families, financial security resources, and mental health support.
- Additional compensation may include an annual performance bonus, equity, or other incentive compensation.
Tech Stack
Apache AirflowApache FlinkApache HadoopApache SparkAWSAzureDockerGitGoogle Cloud PlatformJavaKubernetesMLflowPython
Categories
About PayPal
PayPal builds digital payments platforms for consumers and merchants, including PayPal, Venmo, and Xoom, supporting online, in‑app, and in‑person checkout and peer‑to‑peer transfers. It earns primarily from transaction and merchant processing fees, plus value‑added services such as risk management and branded credit. Founded in 1998 and headquartered in San Jose, California, PayPal operates in roughly 200 markets and is a public company traded on NASDAQ.