Job Title: Machine Learning Engineer III
Duration: 18+ Months
Rate: $50-60/hr on Amtex W2- MAX- Depends on experience.
Location: San Jose (primary), CA or Chicago, IL
What You’ll Do
- Redesign and optimize PayPal’s MLOps and decision platform for fraud detection
- Architect large-scale big-data infrastructure enabling cutting‑edge ML models for real‑time fraud prevention
- Collaborate with data scientists and platform engineers to automate workflows
- Ensure compliance, security, and maintainability across the fraud detection ecosystem
- Work with high‑dimensional datasets using Python, PySpark, and BigQuery for fraud signal detection
- Standardize rules and decision processes while enabling dynamic rule updates and analytics
- Collaborate across engineering, product, and data science teams to scale solutions globally
Team & Project Context
- Works closely with the Core Automation team’s tech leads/managers
- Joins the pioneer team rebuilding PayPal’s Next Generation Risk Platform (NGRP)
- Purpose: build an enterprise‑wide risk platform supporting all business functions, on a tight timeline for decision engine adoption
- Extension/Conversion: No guaranteed extension; possible FTE conversion, but not promised
Typical Day
- Tasks distributed via Jira (sprint planning/grooming)
- Standups at least twice a week (daily if needed/blockers arise)
- Onboarding period requires heavier interaction with Engineering/Product/US Risk core teams; settles into a 50/50 split afterward
- Code hosted in centralized GitHub repo
- Documentation maintained on Wiki or SharePoint/shared drive
Why This Role Is Compelling
Design and implement scalable fraud detection solutions spanning model development, feature engineering, and rule‑based systems — working cross‑functionally with data scientists, engineers, and product managers to set a new global standard. This role offers the chance to build advanced automation frameworks and cutting‑edge ML capabilities that directly protect the financial security of millions of PayPal users worldwide.
Candidate Requirements
Must‑Have Skills (ranked by importance):
- BigQuery, Python
- Understanding of production systems architecture and offline data
- Machine learning experience
Nice to Have: Risk/fraud experience or business acumen; experience working directly with engineers
Experience: 6+ years
Education: Master’s preferred, strong Bachelor’s acceptable — STEM only
Interested candidates send your resume to
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