Senior Machine Learning Engineer

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:

The Braintree Risk Platform Team enables Risk Operations to prevent, detect and safeguard Braintree and its merchants against fraud. In this role you will lead the design, development, and implementation of advanced machine learning models and algorithms to solve complex problems, you will work closely with the software engineers and product teams to enhance our tools through innovative AI/ML solutions.

Job Description:

Essential Responsibilities:

• Lead the development and optimization of advanced machine learning models.
• Oversee the preprocessing and analysis of large datasets.
• Deploy and maintain ML solutions in production environments.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models, making necessary adjustments.

Expected Qualifications:

• Minimum of 8 years of relevant work experience and a Bachelor's degree or equivalent experience.
• Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Preferred Qualification:

Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve fraud and risk management tools. We operate in a cloud environment which requires a deep understanding of cloud storage, computing resources, and networking capabilities. Security is of utmost importance, and we require systems to be operable by mitigating security and operational risks via regular updates to dependencies, frameworks, and code base. We require keeping a low vulnerability score every quarter.

Essential Responsibilities

• You will design projects end-to-end, architecting innovative and cloud-agnostic data solutions.
• Design and implement reliable & scalable AI/ML-powered solutions.
• Translate business problems in the financial domain into technical solutions that leverage machine learning.
• Design data processing pipelines to efficiently ingest, store, and prepare data for AI/ML training and simulation.
• Integrate AI/ML models into existing fintech applications and workflows.
• Document architectural decisions, design patterns and best practices.
• Design and develop machine learning and deep learning systems.
• Running machine learning/artificial intelligence tests and experiments.
• Implementing appropriate ML/AI algorithms.
• Study and transform data science prototypes.
• Research and implement appropriate ML/AI algorithms and tools.
• Develop machine learning/AI applications according to requirements.
• Select appropriate datasets and data representation methods.
• Run machine learning/AI tests and experiments.
• Perform statistical analysis and fine-tuning using test results.
• Train and retrain systems when necessary.
• Extend existing ML/AI libraries and frameworks.

Qualifications

• Experience with model evaluation frameworks and deployment pipelines. (MLFlow, etc.)
• Familiarity with A/B testing and experimentation methodologies
• Proficiency in SQL for data extraction and sampling, familiarity with BigQuery cloud platform, Jupyter Notebooks.
• Proficiency in Python, especially for data manipulation (pandas, numpy) and visualization (seaborn, matplotlib, plotly).
• Strong experience with machine learning libraries (scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch).
• Experience with data cleaning and data pre-processing methods. Experience handling categorical variables, scaling, and encoding techniques (e.g., One-Hot Encoding, Target Encoding).
• Strong understanding of statistics and probability
• Strong understanding of data preprocessing, outlier handling, and missing value treatment.
• Experience designing and implementing stratified sampling techniques.
• Familiarity with correlation analysis, scatterplot matrix generation, and feature interaction studies.
• Knowledge of class imbalance techniques and evaluation metrics
• Excellent communication and mentoring skills, with the ability to explain technical concepts to non-experts.
• Proactive in identifying potential project bottlenecks and providing solutions.

Minimum Qualifications:

• Minimum of 8 years of relevant work experience and a bachelor's degree or equivalent experience.
• Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
• Strong understanding of data management principles and best practices.
• Experience designing and implementing data pipelines for AI/ML projects.

Nice to have:

Fraud Detection Knowledge - Experience working with fraud or anomaly detection models is highly preferred.