Sr Machine Learning Engineer

Job Summary

This job is responsible for independently validating and providing oversight of high-impact statistical, machine learning, and AI models across key business areas such as credit, fraud, marketing, and collections. It involves assessing model soundness, data quality, and performance to identify and mitigate model risk, while collaborating with developers and business partners on remediation and improvement. The position also supports AI and model risk governance to ensure compliance with Pay Pal’s enterprise risk framework and evolving regulatory standards.

• 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.

• 3+ years relevant experience and a Bachelor’s degree OR any equivalent combination of education and experience.
• Experience with ML frameworks like Tensor Flow, 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.

• Advanced degree (Master's or Ph.D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field.
• Strong knowledge of statistical and machine learning techniques, including but not limited to logistic regression, time‑series modeling, random forests, support vector machines, gradient boosting (e.g., XGBoost), and deep learning architectures (e.g., CNNs, RNNs).
• Proficiency in programming and big‑data technologies, with hands‑on experience in tools such as Python (Scikit‑learn, Tensor Flow), SQL, Hadoop, and Spark.
• Relevant modeling experience in one or more of the following domains: credit risk scoring, fraud detection, financial forecasting, or marketing analytics – gained through industry or academic research.
• Strong collaboration and communication skills, with the ability to work effectively both independently and as part of a cross‑functional team.
• Ability to articulate complex technical concepts clearly to non‑technical stakeholders and build constructive working relationships across functions.
• Experience with Large Language Models (LLMs), Agentic AI, or related generative AI applications.
• Familiarity with model governance, model risk management, or AI regulatory compliance frameworks (e.g., SR 11-7, OCC 2011‑12, EU AI Act) is a plus.

Primary Location – Chicago, Illinois: $ – $ Annually

Additional Location – San Jo— $ – $ Annually

Additional Location – Austin, Texas: $ – $ Annually

Pay Pal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, Pay Pal will provide reasonable accommodations for qualified individuals with disabilities.

If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalgloba