Senior / Staff Machine Learning Engineer, Fraud

We're looking for Product Engineers to build machine learning-based anti-fraud systems into core Radar products. The ideal engineer for this role is someone who is primarily an ML engineer, and has built fraud detection models but wants to broaden their skills into other stacks like server or data. The perfect candidate will see themselves as a generalist who has built real ML systems and is ultimately motivated by driving impact to products and customers by building end-to-end features that leverage machine learning to prevent fraud.

We care a lot about shipping fast and talking to customers. We're committed to our product vision of full-stack location infrastructure, but we also know that customer feedback is a treasure map to gold. Even though Slack is the brain of our company, working together in-person in our NYC HQ is the fastest way for us to get things done.

We meet on Mondays to plan out work for the week in small groups and use Linear for planning.

To us, a week is a long time, and we expect to ship big things every week.

We have systems that leverage LightGBM and random forests using scikit and Rust and we need to build out new systems impacting additional products.

The server is a TypeScript Node.js app and a Geospatial Rust database we built called HorizonDB. We use MongoDB, S3/Athena, Redis, Airflow and everything is deployed to AWS.

- Work on core Radar ML infrastructure built with Python, Rust, Airflow, Spark and new systems you build

- Build new systems for our Fraud products: anomaly detection, user and device risk scores, device fingerprinting, and emerging threat vectors

- Work on features across several of backend, data infra and ML

- Push the limits of fraud detection using many sensors on iOS and Android

- Talk to Radar customers and prospects, hear their feedback, incorporate it into your work, and make them successful

- Have experience building machine learning based fraud detection products in production at scale

- Are deeply curious about how things work, and have the tenacity to sit with hard problems and power through them

- Have experience with anomaly detection, anti-fraud ML systems

- David Gurevich https://www.linkedin.com/in/davidgur/, Engineer