Machine Learning Engineering

Job Description

Job Description (JD) – Machine Learning Engineering Lead | PayPal
Company

PayPal is a global digital payments and financial technology company operating in approximately 200 markets. For over 25 years, PayPal has enabled secure online and in-person payments, money transfers, merchant solutions, and financial services for consumers and businesses worldwide.

Job Title

Machine Learning Engineering Lead (Risk Management – Data Science Team)

Job Summary

PayPal is seeking an experienced Machine Learning Engineering Lead to design, develop, deploy, and optimize advanced machine learning solutions for fraud risk management. The role involves leading ML initiatives, building scalable production systems, mentoring engineers, and collaborating with cross-functional teams to improve customer experience while minimizing fraud risk.

Team

Risk Management – Data Science Team

The team develops AI and Machine Learning solutions that automate operational reviews for fraud detection and risk management while balancing innovation, regulatory compliance, fraud prevention, and customer experience.

Key Responsibilities
Machine Learning Development
Design and develop advanced machine learning models.
Build scalable ML pipelines and production-ready AI solutions.
Optimize machine learning algorithms for business applications.
Analyze and preprocess large-scale datasets.
Extract business insights using statistical and machine learning techniques.
Monitor model performance and continuously improve prediction accuracy.
Deploy machine learning models into production environments.
Cross-functional Collaboration
Work closely with:
Product Managers
Data Scientists
Software Engineers
Business Stakeholders
Integrate ML models into PayPal products and services.
Understand evolving business requirements and translate them into AI solutions.
Leadership Responsibilities
Lead execution of ML engineering projects.
Mentor and guide team members.
Improve team capabilities and technical excellence.
Ensure timely project delivery.
Support career development of engineers.
Required Qualifications
Bachelor’s degree in:
Computer Science
Artificial Intelligence
Machine Learning
Data Science
Engineering
or equivalent practical experience.
Minimum 8 years of relevant industry experience.
Required Technical Skills
Machine Learning
Machine Learning model development
Model optimization
Model deployment
Feature engineering
Data preprocessing
Model evaluation
ML Frameworks
TensorFlow
PyTorch
Scikit-learn
Cloud Platforms

Experience with one or more:

AWS
Microsoft Azure
Google Cloud Platform (GCP)
ML Engineering
Production ML systems
Model deployment
ML pipelines
Data processing
Scalable AI systems
Data Engineering
Large dataset processing
Data quality management
Feature engineering
Leadership Skills
Technical leadership
Team mentoring
Project ownership
Stakeholder management
Cross-functional collaboration
Decision making
Preferred Experience
Building production-scale ML systems
Fraud Detection
Risk Analytics
Financial Technology (FinTech)
AI-powered decision systems
Distributed ML infrastructure
Work Model
Hybrid Work
3 days in office
2 days remote/home
Benefits

PayPal offers:

Flexible hybrid work model
Employee stock/share options
Health insurance
Life insurance
Wellness programs
Financial wellbeing benefits
Learning and development opportunities
Inclusive work environment
Career growth opportunities
Minimum Experience
8+ years in Machine Learning Engineering or related fields.
Ideal Candidate Profile

Candidates should have expertise in:

Machine Learning Engineering
TensorFlow / PyTorch / Scikit-learn
Cloud Platforms (AWS, Azure, GCP)
Production ML deployment
Large-scale distributed systems
Fraud detection or Risk Analytics (preferred)
Team leadership and mentoring
Recruitment Note

PayPal does not charge any fees for:

Job applications
Interviews
Resume reviews
Background verification
Onboarding

Any request for payment during the recruitment process should be treated as fraudulent.