Staff Machine Learning Engineer

PayPal•San Jose, CA

2d•$227,639 - $300,500•Hybrid

About The Position

PayPal, Inc. seeks Staff Machine Learning Engineer in San Jose, CA. The role involves designing and deploying scalable Risk analytical solutions and generative AI solutions, and productizing Machine Learning models to enhance customer experience. The engineer will lead and collaborate with data scientists and system engineers to solve complex problems using machine learning and AI. Key responsibilities include defining technical standards, ensuring code quality, driving innovation by researching and incorporating state-of-the-art ML techniques, leading architecture design, and developing AI agents for workflow automation and issue detection. The role also includes mentoring team members and fostering a collaborative culture. Partial telecommuting is permitted.

Requirements

Master’s degree, or foreign equivalent, in Computer Science, Engineering, or a closely related field plus five years of experience in the job offered or a related occupation. OR Bachelor’s degree, or foreign equivalent, in Computer Science, Engineering or a closely related field plus eight years of progressively responsible experience in the job offered or a related occupation.
Experience designing and deploying scalable machine learning models and pipelines in production environments using Python and Java (4 years)
Experience developing and productizing Generative AI solutions, including LLMs, RAG pipelines, or AI agents (e.g., LangChain, LlamaIndex, or similar frameworks) (2 years)
Experience with big data technologies and distributed computing frameworks such as Spark, Hadoop, or Flink for large-scale data processing (3 years)
Experience designing and developing large-scale software applications using Object-Oriented Design in Java or Python (4 years)
Experience with cloud platforms (AWS, GCP, or Azure) for deploying and managing ML/AI workloads, including containerization with Docker and Kubernetes (2 years)
Experience building and maintaining data pipelines and ML feature engineering systems using tools such as Airflow, MLflow, or similar MLOps platforms (2 years)
Experience in risk analytics or fraud detection domains, including model development for anomaly detection, payment risk, or transaction monitoring (2 years)
Experience developing AI agents or workflow automation systems using agentic frameworks for issue detection, root cause analysis, or automated remediation (1 year)
Experience with software engineering best practices including code reviews, unit/integration testing, CI/CD pipelines, and version control (e.g., Git) (4 years)
Experience leading cross-functional teams of data scientists, product managers, and system engineers to deliver end-to-end ML/AI solutions in a matrix organization (3 years)
Must be legally authorized to work in the U.S. without sponsorship.

Responsibilities

Design and deploy scalable Risk analytical solutions and generative AI solutions.
Productize Machine Learning models that enhance PayPal's ability to provide a seamless customer experience.
Lead and collaborate with data scientists and system engineers to solve complex problems with machine learning and AI capabilities.
Define technical standards and ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices.
Drive innovation by researching and incorporating state-of-the-art machine learning techniques, tools, and frameworks into the platform.
Lead architecture design and technical decision-making across cross-functional groups and deliver results in matrix organizations.
Develop different AI agents to automate workflow, detect live issues and provide fix suggestions.
Mentor senior and junior team members, provide technical guidance and strategic direction, and foster a culture of collaboration, innovation, and continuous learning.