Senior / Staff Machine Learning Engineer, Fraud

About the role

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.

How We Work

• Most of our engineering team are former technical co-founders or former Radar interns from schools like Waterloo and CMU.
• Most engineers at Radar fit one of two molds, technically: either Staff level expertise in one stack, or "Multi-Stack" at any level.
• 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.
• 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.

The Stack

• 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.
• Most engineers are in the on-call rotation.

What You’ll Do

• 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 MLPush 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.

What You Should Have

• Experience building machine learning based fraud detection products in production at scale.
• Interest in talking to customers or prospects and making them successful.
• Deeply curious about how things work, and have the tenacity to sit with hard problems and power through them.

Bonus Points

• If You Are a former technical co-founder.
• If You Have experience with anomaly detection, anti-fraud ML systems.

What We Offer

• Competitive salary
• Meaningful stock options in a fast-growing company
• 401(k) plan with 4% match
• New HQ in Flatiron, NYCTop-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

Compensation

For candidates based in the United States, the base salary range for this full-time position is between $200,000 - $300,000/year with an opportunity for performance bonuses and incentives. In addition to cash compensation, Radar offers full-time employees stock option grants under its equity plan. This is a meaningful ownership stake in the company we provide to our employees as we build a category-defining company. Our salary ranges are determined by role, level, and location. The range displayed on this job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Your exact offer may vary based on market location, job-related skills, experience, and relevant education or training.