Senior / Staff Product Engineer, Machine Learning
Builds ML-based systems integrated into Radar's geofencing, maps, and fraud products across backend, data infra, and mobile SDKs. Drives end-to-end features leveraging ML for production-scale impact, collaborates with customers.
About the job
Responsibilities
- Work on core Radar ML infrastructure built with Python, Rust, Airflow, Spark and new systems.
- Build new systems for Fraud products: anomaly detection, user and device risk scores, device fingerprinting, and emerging threat vectors.
- Build new systems for Maps products: search ranking and query classification for addresses, points of interest leveraging "learn-to-rank" systems, LightGBM; create road traffic models to improve ETA accuracy; leverage AI to ingest address and POI data.
- Build new systems for Geofencing products: indoor positioning leveraging mobile device sensors (BLE, barometer, motion, Ultra-Wideband).
- Work on full-stack features across backend, data infra, mobile, and frontend.
- Push limits of location services on iOS and Android.
- Talk to customers and prospects, incorporate feedback.
Requirements
- Experience building machine learning based products in production at scale.
- Don't think of yourself as an "ML Engineer".
- Interested in talking to customers or prospects and making them successful.
- Deeply curious about how things work, tenacity to power through hard problems.
Nice-to-Haves
- Former technical co-founder.
- Experience with anomaly detection, indoor positioning, or mapping infrastructure.
Compensation
- Base salary $200,000 - $300,000/year.
- Performance bonuses and incentives.
- Stock option grants.
- 401(k) with 4% match.
- Health, dental, vision insurance (100% coverage).
- 12 weeks paid parental leave.
- Unlimited PTO, commuter/fitness benefits.
Skills
Python, Rust, Airflow, Spark, Lightgbm, scikit-learn, TypeScript, Node.js, MongoDB, Redis, AWS, Kubernetes, Machine Learning, Anomaly Detection, Indoor Positioning
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