PayPal is looking for a Machine Learning Engineer (MLE) Apprentice – Residency 3 to build and optimize production ML systems that secure our global payments platform. In this role, you will operate with increased autonomy, taking end-to-end ownership of well-scoped components that balance accuracy, latency, and security.
What You'll Do
- Own and deliver defined components of production ML systems end to end.
- Optimize ML models and data pipelines for performance, scalability, and reliability.
- Partner with platform and infrastructure teams on deployment and production readiness.
- Evaluate trade-offs between model complexity, explainability, and latency.
- Implement monitoring, testing, and validation for ML solutions.
- Apply security, privacy, and ethical AI principles in system design.
- Present outcomes, insights, and recommendations to engineering and leadership audiences.
What We're Looking For
- Currently enrolled in a Computer Science, Engineering, Data Science, AI, or related degree (2nd year).
- Strong foundation in machine learning and software engineering.
- Experience building or optimizing ML models and pipelines.
- Proficiency in Python and SQL.
- Understanding of system design, APIs, and production engineering concepts.
- Ability to work independently on complex technical problems.
- Strong communication skills and an ownership-driven mindset.
- Passion for AI, Fraud and Innovation.
Nice to Have
- Exposure to distributed or real-time systems is a plus.
Technical Stack
- Python
- SQL
Benefits & Compensation
- Comprehensive, choice-based programs supporting personal wellbeing—physical, emotional, and financial.
- Generous paid time off.
- Healthcare coverage for you and your family.
- Resources to create financial security and support your mental health.
Work Mode
This is a hybrid position based in our Dublin office.
PayPal 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.
