Senior / Staff Product Engineer, Machine Learning

Radar•New York, NY

1d•$200,000 - $300,000•Onsite

About The Position

We're looking for Product Engineers to build machine learning-based systems into core Radar products. This is a product-oriented role building new machine learning based systems into our backend, data infra, and mobile SDKs. The ideal engineer for this role is someone who is primarily an ML engineer but wants to broaden their skills into other stacks like server, data and mobile. The perfect candidate will see themselves as 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. We have many ML challenges across our Geofencing, Maps and Fraud products.

Requirements

Have experience building machine learning based products in production at scale
Don't think of yourself as an "ML Engineer"
Are interested in talking to customers or prospects and making them successful
Are deeply curious about how things work, and have the tenacity to sit with hard problems and power through them

Nice To Haves

Are a former technical co-founder
Have experience with anomaly detection, indoor positioning, or mapping infrastructure

Responsibilities

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
Build new systems for our Maps products: search ranking and query classification for addresses, points of interest and others leveraging "learn-to-rank" systems, LightGBM, and new systems you build. Create road traffic models based on historical and live data to improve the ETA accuracy of our routing engine. Leverage AI to ingest address and point-of-interest data from across the web.
Build new systems for our Geofencing products: indoor positioning leveraging mobile device sensors (BLE, barometer, motion, ultra-wideband, etc)
Work on full-stack features across several of backend, data infra, mobile, and frontend
Push the limits of what is possible with location services on iOS and Android
Have your work run on 300M+ devices
Talk to Radar customers and prospects, hear their feedback, incorporate it into your work, and make them successful