MTS 1, Machine Learning Engineer

What you need to know about the role-

This role involves designing and implementing Machine Learning solutions in the Payments domain at PayPal Scale. The candidate needs to have hands-on experience in working with Big Data technologies such as Apache Spark, Hadoop based ecosystem tools and frameworks and understands end to end to Model Development Life cycle. Professional experience in writing production grade Scala/Python code as well SQL is mandatory. Understanding of Cloud Native technologies and experience in one the Cloud Platforms such as GCP/Azure/AWS is highly recommended. Experience in building and deploying production grade Generative AI Applications is a plus.

Meet our team

The Payments ML Engineering team as part of Consumer and Merchant Solutions (CMS) Team as part of AI, ML Platform Solutions (AMPS) Org is focussed on improving the Authorization Rate and Transaction Expense Savings contributing to more than $75M revenue through various prediction and optimization problems that could be solved using ML. The team also contributes to various ML Platform features such as Feature Marts, Model monitoring products at PayPal.

• Design and build production grade ML applications from Data Preparation, Feature Engineering, Model Training and Evaluation and Deployment.
• Highly effective at working in cross-functional groups including Data Scientist, ML Engineers, Software Engineers, QA Engineers and Product Managers to build and deploy ML and Gen AI based applications.
• Highly analytical, innovative, and able to think strategically and to develop detailed technical specifications based on Product Requirements Documents.

• Write clean, high-performance, high-quality, maintainable code in Python/Scala and SQL.
• Discovering, analyzing, structuring and mining data
• Be a key engineer contributing to the design, development of the new functionalities and maintaining the existing components
• Work with data scientists and backend engineers to implement scalable AI and ML solutions to solve complex problems at scale.
• Maintain and enhance the existing architectural and design documentations and create the new one as needed

• Excellent communication skills (both oral and written) to communicate highly technical work and decision to our Business, Data science partners and Leadership
• Proven experience in designing and deploying ML/AI solutions at scale in the payments or a similar domain.
• Strong proficiency in big data technologies such as Apache Spark, Hadoop, and distributed computing frameworks.
• Hands-on expertise with cloud-native ML tools and platforms, particularly Vertex AI, and experience deploying models in cloud environments (e.g., Google Cloud, AWS, or Azure).
• Excellent programming skills in Python, Scala, or Java, with experience in ML libraries such as TensorFlow, PyTorch, or Scikit-learn.
• Deep understanding of the end-to-end model development lifecycle, including data wrangling, feature engineering, model evaluation, and monitoring.
• Strong problem-solving and analytical skills, with a passion for tackling complex business challenges.

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