PayPal Sr Machine Learning Engineer 

United States, Illinois, Chicago 

557730200

Responsibilities:Model Development: Design and implement core decision models for identity, onboarding, authentication, abuse, scam, product-specific models.Anomaly Detection: Develop and refine algorithms for detecting anomalies and identifying potential fraud patterns.Supervised Learning: Apply supervised learning techniques to build predictive models that accurately identify fraudulent activities.Continuous Learning: Utilize continual learning methods to continuously improve model performance and adapt to new fraud tactics.Experimentation and Analysis: Conduct experiments, analyze results, and interpret findings to drive innovation and enhance decision-making processes.

Essential Responsibilities:

• 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.

Minimum Qualifications:

• Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
• Experience with ML frameworks like TensorFlow, 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.

• Expertise : Familiarity with decision models for identity and authentication.
• Domain Knowledge : Experience in fraud prevention and detection.
• Instrumentation : Experience driving data instrumentation for experimentation and large-scale data collection.
• Real-time Systems : Familiarity with building systems that incorporate real-time feedback and continuous learning.
• Advanced Techniques : Knowledge of reinforcement learning, contextual bandits, sequence models, optimization, or graph mining.
• Education : Master's degree or PhD in Computer Science, Statistics, Data Science, Machine Learning, Artificial Intelligence, or a related quantitative field (STEM).
• Experience : 5+ years of experience within ML Engineering or AI Research roles, with demonstrated expertise in building and deploying real-world predictive models.
• Skills : Strong understanding of anomaly detection, supervised learning techniques, and experiential learning methods. Experience in fraud prevention is a plus.
• Communication : Strong interpersonal, written, and verbal communication skills, with experience collaborating across multiple business functions.

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 $137,500 to $236,500

Our Benefits:

Any general requests for consideration of your skills, please