Radar
Senior / Staff Machine Learning Engineer, Fraud
New York · Staff+ · Full-time
H1B sponsorship available$200k-$300kDetected 138 days ago
TypeScriptPythonRustiOSAndroidNode.jsFull-Stack DevelopmentMongoDBRedisMachine LearningSparkAirflowProduct StrategyCustomer SuccessSensors
About the role
- 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.
- 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.
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
- This is a meaningful ownership stake in the company we provide to our employees as we build a category-defining company.
Nice to have
- Are a former technical co-founder
- Have experience with anomaly detection, anti-fraud ML systems
Skills
- Most engineers are in the on-call rotation.
- Engineers choose what AI tools they use, Claude and Codex being the most popular.
- There is a range of how much engineers use AI. Most use it daily if not weekly.
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.
- Our salary ranges are determined by role, level, and location.
- Competitive salary
Benefits
- Meaningful stock options in a fast-growing company
- Health, dental, and vision insurance with 100% coverage for employees
- 12 weeks of paid parental leave
- Commuter and fitness benefits
Company info
- 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
- Nick Patrick https://www.linkedin.com/in/nicholaspatrick/, Co-Founder and CEO
- Tim Julien https://www.linkedin.com/in/timjulien/, CTO
- David Gurevich https://www.linkedin.com/in/davidgur/, Engineer
- Our customers and prospects
- Our Customer Success, Sales Engineering, and Sales teams
- 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.
- We care a lot about shipping fast and talking to customers.
- 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 are excited about what AI can do, but we also recognize the risks and don't compromise our coding standards.
- Talk to Radar customers and prospects, hear their feedback, incorporate it into your work, and make them successful
Equal opportunity
- We are proud to be an equal opportunity workplace.
Visa & Work Authorization
- al employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status
This listing is sourced directly from Radar's careers page and normalized into a canonical job model.