Senior / Staff Product Engineer, Machine Learning

About the role

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.

Responsibilities

• Work on core Radar ML infrastructure built with Python, Rust, Airflow, Spark 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 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
• 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
• Talk to Radar customers and prospects, hear their feedback, incorporate it into your work, and make them successful

Requirements

We're looking for someone who has 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.

Qualifications

• Experience with anomaly detection, indoor positioning, or mapping infrastructure is a plus

Skills

• Strong understanding of machine learning algorithms and techniques
• Experience with Python, Rust, Airflow, Spark, and related technologies
• Experience with building and deploying machine learning models in production
• Experience with building and deploying systems in a cloud environment (AWS)
• Experience with building and deploying systems in a multi-stack environment (backend, data infra, mobile, frontend)
• Experience with building and deploying systems in a distributed environment
• Experience with building and deploying systems in a collaborative environment (working with multiple stakeholders)

Benefits

• Competitive salary
• Meaningful stock options in a fast-growing company
• 401(k) plan with 4% match
• New HQ in Flatiron, NY
• Top-notch equipment
• Catered lunches
• Unlimited PTO
• Health, dental, and vision insurance with 100% coverage for employees
• 12 weeks of paid parental leave
• Commuter and fitness benefits

Pay

The base salary range for this full-time position is between $200,000 - $300,000/year with an opportunity for performance bonuses and incentives.

Schedule

This is a full-time position.