PayPal Sr Machine Learning Engineer 

United States, California, San Jose 

567560515

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Essential Responsibilities:

• Develop and optimize machine learning models for various applications.
• Preprocess and analyze large datasets to extract meaningful insights.
• Deploy ML solutions into production environments using appropriate tools and frameworks.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models.

Minimum Qualifications:

• Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
• Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
• Several years of experience in designing, implementing, and deploying machine learning models.

• Expertise in data modeling, feature engineering, and a strong grasp of traditional machine learning algorithms (e.g., Neural Networks, Linear Regression, Logistic Regression, Random Forest, etc.).
• Experience with Large Language Models (LLMs), particularly in areas like RAG, MCP, and Agentic Agents.
• Experience in containerization tools like Docker and Kubernetes. GCP experience is a distinct advantage.
• Strong proficiency in SQL, ETL processes, and database design, with practical knowledge of NoSQL systems like HBase, Redis, and Aerospike.
• Solid understanding of distributed systems, real-time data streaming, and complex event processing architectures.
• Knowledge of front-end and back-end development; full-stack engineering experience is a plus.

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

The US national annual pay range for this role is $137,500 to $236,500

Our Benefits:

Any general requests for consideration of your skills, please