Machine Learning Engineer II (Fraud)
Affirm · Remote (Canada) · Checkout
About this role
Affirm is hiring a mid-level Machine Learning Engineer as a remote position. The posting calls out experience with Python, Spark, Airflow, PyTorch. Compensation is listed at $125,000–$175,000 per year.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Remote (Canada)
- Work mode
- Remote
- Department
- Checkout
More roles at Affirm
Job description
from Affirm careersAffirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
On the ML Fraud team, you’ll build and improve machine learning systems that make real-time transaction decisions, protecting consumers and merchants while balancing fraud loss, customer experience, and conversion. You’ll work closely with experienced ML engineers, platform partners, and cross-functional stakeholders to take models from idea to prototype to production, and to keep them healthy with strong measurement and monitoring as fraud patterns evolve.
What you’ll do
- You will develop and iterate on fraud prediction models using a mix of approaches for tabular and behavioral data
- You will build and scale feature pipelines and training datasets from proprietary and third-party signals, partnering with data and platform teams when needed.
- You will prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
- You will help productionize models: integrate into batch and/or real-time decision systems, and improve reliability, latency, and operational robustness.
- You will instrument and monitor model and data health, and help define retraining/backtesting workflows as fraud patterns evolve.