Staff ML Engineer - Generative AI & Risk Analytics Lead

PayPal; San Jose (CA); Hybrid; USD 228,000 - 301,000; Full time

Job summary

PayPal, Inc. seeks a Staff Machine Learning Engineer in San Jose, CA to design and deploy scalable risk analytics solutions and generative AI models that enhance the PayPal customer experience.

You will lead and collaborate with data scientists and engineers to solve complex ML problems, drive architecture decisions, and advance AI capabilities across the platform. This role offers a balanced hybrid work model and opportunities for mentor and growth.

Qualifications

• Master's degree or foreign equivalent in Computer Science, Engineering, or closely related field +5 years experience in ML/AI roles.
• Bachelor's degree or foreign equivalent +8 years experience accepted as alternative.

Responsibilities

• Design and deploy scalable risk analytics solutions and generative AI models.
• Lead collaboration with data scientists and system engineers to solve ML problems.
• Define technical standards and ensure high code quality and reliability through testing and reviews.
• Research and incorporate state-of-the-art ML techniques and frameworks.
• Lead architecture design across cross-functional groups and drive outcomes.
• Mentor senior/junior team members and foster collaboration and learning.

Skills

Python

Java

Generative AI

LangChain

LlamaIndex

Big data processing

Spark

Hadoop

Flink

Cloud platforms

Docker

Kubernetes

Airflow

MLflow

MLOps

Risk analytics

Anomaly detection

CI/CD

Git

Team leadership

Education

Master's degree in CS/Engineering

Bachelor's degree in CS/Engineering

Tools

Spark

Hadoop

Flink

LangChain

LlamaIndex

Docker

Kubernetes

Airflow

MLflow

Git

Job description

PayPal, Inc. seeks a Staff Machine Learning Engineer in San Jose, CA to design and deploy scalable risk analytics solutions and generative AI models that enhance the PayPal customer experience.

You will lead and collaborate with data scientists and engineers to solve complex ML problems, drive architecture decisions, and advance AI capabilities across the platform. This role offers a balanced hybrid work model and opportunities for mentor and growth.