Sr Machine Learning Engineer

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The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do - and they push us to ensure we take care of ourselves, each other, and our communities. Job Summary: Job Description: PayPal, Inc. seeks Sr Machine Learning Engineer in Austin, TX Job Duties: Evaluate and validate high-impact statistical and AI/ML models across key business areas. Perform comprehensive quantitative and qualitative model validation in alignment with internal Model Risk Management (MRM) Policy and industry standards. Assess model data integrity, design soundness, and performance robustness to identify and report potential risks and deficiencies. Provide risk oversight on the engineering, automation, and production deployment of sophisticated machine learning models. Build scalable systems with Python and cloud platforms, and architect end-to-end pipelines for real-time data ingestion, model serving, and monitoring. Lead technical projects, coordinate project roadmaps, and mentor junior engineers while integrating cutting-edge methods in deep learning and generative AI. Ensure system reliability, regulatory compliance, and technical innovation through collaboration with DevOps, IT, and business partners. Drive transformative change across products and services through continuous improvement, advanced model tuning, and implementation of system-wide best practices for performance, scalability, and ethical AI use. Partial telecommuting permitted from within a commutable distance. Minimum Requirements: Master's degree, or foreign equivalent, in Data Science, Computer Science, Business Analytics, or a closely related field plus two years of experience in the job offered or a related occupation. Special Skill Requirements: 1. Experience designing and implementing scalable machine learning models using algorithms such as logistic regression, random forests, gradient boosting, and time series models to solve business problems (2 years). 2, Experience utilizing deep learning and Generative AI architectures, including CNNs, RNNs, and large language models (LLMs), to enhance automation and decision-making (2 years). 3. Experience conducting exploratory data analysis (EDA), statistical modeling, and visualization to identify trends, detect anomalies, and inform model improvements (2 years). 4. Experience programming in Python for model development, validation, and automation using libraries such as pandas, scikit-learn, TensorFlow, and PyTorch (2 years). 5.Experience writing and optimizing complex SQL queries for data extraction, transformation, and analytics in large-scale environments (2 years). 6. Experience developing, validating, and maintaining statistical and AI/ML models for risk management, fraud detection, AML, and compliance in alignment with Model Risk Management (MRM) standards (2 years). 7. Experience performing comprehensive model validation, including data quality assessment, benchmarking, back-te

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