PayPal Staff Machine Learning Engineer 

United States, California, San Jose 

32808093

What you need to know about the role
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.

Job Description:

Your way to impact

• Highly effective at working in cross-functional groups and getting results in matrix organizations
• Mentor team members, provide, technical guidance, and foster a culture of collaboration, innovation, and continuous learning.

Your day-to-day

• Design and deploy scalable traditional and generative AI solutions and productize ML models that enhance PayPal's ability to provide a seamless customer experience
• Work with data scientists and backend engineers to solve complex problems with AI/ML.
• 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.

What do you need to bring

• At least 5 years of relevant industry experience in machine learning or data engineering.
• Bachelor’s degree in computer science, engineering, or a related field (or equivalent experience).
• Proficient in one or more programming and scripting languages, such as Python, Java, Scala, and Unix/Linux shell scripting.
• Solid understanding of machine learning concepts, algorithms, and techniques, with hands-on experience in developing, training, and deploying ML models.
• Experience using popular ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Familiarity with major cloud platforms (GCP, AWS, or Azure).
• Proven experience designing, implementing, and deploying end-to-end machine learning solutions in production environments.
• Extensive experience with big data technologies such as Hadoop, Apache Spark, HBase, and Kafka.
• Strong background in distributed systems, real-time data streaming, and complex event processing.
• Hands-on experience with NoSQL databases and building robust data integration pipelines for both batch and streaming data.
• Exceptional analytical and problem-solving skills, particularly in identifying root causes of production issues using big data platforms.
• Familiarity with large language models (LLMs), including RAG, MCP, and Agentic Agents.

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 $169,500 to $291,500

Our Benefits:

Any general requests for consideration of your skills, please