Senior / Staff Machine Learning Engineer, Fraud

Why is Radar the best place to work?

• We're trusted by some of the world's best companies, from high-growth startups to the Fortune 500.
• We have incredible scale: We're processing over 1 billion API calls per day from hundreds of millions of devices.
• We're well-resourced, and we've raised $85.5M from world-class investors, including Accel and Insight Partners.
• We have a high-performance culture, with ambitious and entrepreneurial teammates in every role.
• We recently moved into an amazing new office in Flatiron, Manhattan, NYC.
• We were recently named a top 10 best place to work in NYC by Crain's.

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 has built ML based fraud detection models, leveraged in a risk based rules engine. 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.

How we work:

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.

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 ML
• Push the limits of fraud detection using many sensors 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

You should:

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

Bonus points if you:

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

You’ll work with:

• Nick Patrick, Co-Founder and CEO
• Tim Julien, CTO
• David Gurevich, Engineer
• Our customers and prospects
• Our Customer Success, Sales Engineering, and Sales teams

What we offer:

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

Radar is an equal opportunity employer and does not discriminate on the basis of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, veteran status, or any other characteristic protected by law.