Radar Jobs Hiring Now
Radar is hiring for 11 open roles on Migrate Mate as of October 15, 2026, concentrated in software engineering and product management, with listed salaries up to about $300,000. Migrate Mate updates Radar's live openings daily. Radar is a location technology company that builds geofencing, geocoding, and real-time location infrastructure used by developers and enterprise teams across industries.
Find Radar JobsOverview
Radar hiring data on Migrate Mate, as of October 15, 2026.
- Open jobs
- 11
- Top team
- Software Engineering
- Seniority
- Manager level or above
- Work type
- 45% remote or hybrid
- Top location
- New York
- Salary range
- $125,000–$300,000
Listed salaries for Radar roles on Migrate Mate range from about $125,000 to $300,000 per year across 11 open roles, as of October 15, 2026.
Open Roles at Radar
Showing 11 of 11+ Radar jobs
About Radar
Radar is the global leader in geolocation, with geofencing SDKs, maps APIs, and AI-enabled solutions for marketing, fraud, and operations teams. 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.
Despite our growth and scale, we're still just getting started. That's where you come in.
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. 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
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 say "Multi-Stack" because "Full-Stack" has the connotation of "Frontend and Backend", but Radar Engineers might also work on Mobile or Data engineering. Not that you need to be an expert in all of those, but a desire to learn, jump around to different stacks, and get things done is the important part. 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. 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.
How We Use AI
Engineers choose what AI tools they use, Claude and Codex being the most popular.
We're actively building Claude skills - for example we've taught it how to debug HorizonDB, our geospatial database.
All code changes are reviewed by an Engineer knowledgeable in that area. Claude and Codex also review all PRs.
There is a range of how much engineers use AI. Most use it daily if not weekly.
* We are excited about what AI can do, but we also recognize the risks and don't compromise our coding standards.
The Hiring Process
After a call with our Technical Recruiter, you'll do several technical Zoom calls with members of our engineering team: code screen, coding round, and system design round. If those go well we'll invite you to our NYC HQ for a final round interview. You'll meet one of our co-founders, someone from outside engineering, and meet more people from Radar. We'll go into more depth about how we work to see if there is a match.
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
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.
We are committed to equal 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. We are proud to be an equal opportunity workplace.
Compensation Range: $200K - $300K
About Radar
Radar is the global leader in geolocation, with geofencing SDKs, maps APIs, and AI-enabled solutions for marketing, fraud, and operations teams. 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.
Despite our growth and scale, we're still just getting started. That's where you come in.
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. 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
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 say "Multi-Stack" because "Full-Stack" has the connotation of "Frontend and Backend", but Radar Engineers might also work on Mobile or Data engineering. Not that you need to be an expert in all of those, but a desire to learn, jump around to different stacks, and get things done is the important part. 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. 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.
How We Use AI
Engineers choose what AI tools they use, Claude and Codex being the most popular.
We're actively building Claude skills - for example we've taught it how to debug HorizonDB, our geospatial database.
All code changes are reviewed by an Engineer knowledgeable in that area. Claude and Codex also review all PRs.
There is a range of how much engineers use AI. Most use it daily if not weekly.
* We are excited about what AI can do, but we also recognize the risks and don't compromise our coding standards.
The Hiring Process
After a call with our Technical Recruiter, you'll do several technical Zoom calls with members of our engineering team: code screen, coding round, and system design round. If those go well we'll invite you to our NYC HQ for a final round interview. You'll meet one of our co-founders, someone from outside engineering, and meet more people from Radar. We'll go into more depth about how we work to see if there is a match.
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
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.
We are committed to equal 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. We are proud to be an equal opportunity workplace.
Compensation Range: $200K - $300K
Job Roles at Radar
Working at Radar
Radar's 11 open roles are manager level or above, and about 45% are remote or hybrid. The most active teams are software engineering, product management, and cloud & DevOps. Radar builds location infrastructure products, including geofencing APIs, address autocomplete, and trip tracking tools used by engineering and product teams to power location-aware applications. Its open roles span engineering, security, product, marketing, and operations functions. Most Radar roles are based in New York and Remote.
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Browse jobs by roleRadar Jobs: Frequently Asked Questions
How many jobs is Radar hiring for right now?
Radar is hiring for 11 open roles on Migrate Mate as of October 15, 2026, updated daily, concentrated in software engineering and product management. Roles span engineering, security, product marketing, operations, and executive support, reflecting active hiring across both technical and business functions.
What kinds of roles does Radar hire for?
The most active teams are software engineering, product management, and cloud & DevOps. Radar's open positions include software and systems engineering, site reliability, security, product management, product marketing, fraud operations, and executive support. The mix covers both hands-on technical contributors and senior leadership, and most postings are manager level or above.
Are Radar jobs remote or in-person?
A mix of remote and on-site. About 45% of Radar's open roles on Migrate Mate are remote or hybrid as of October 15, 2026, with the rest based in New York. Each Radar listing shows its work location so you can filter before applying.
How do I apply to a job at Radar?
Find a role that matches your background on Migrate Mate, then follow the listing through to Radar's own careers page to submit your application directly. Radar manages its own hiring process, including application review, interviews, and offers, entirely on its end.
What do Radar jobs pay?
Listed salaries for Radar roles on Migrate Mate range from about $125,000 to $300,000 per year as of October 15, 2026, with most postings at manager level or above. Exact pay is set by Radar and shown on each listing.
Does Radar hire entry-level?
Most of Radar's open roles on Migrate Mate are manager level or above as of October 15, 2026. Entry-level openings are limited. Check individual Radar listings for stated experience requirements.
Where is Radar hiring?
Most Radar roles are based in New York and Remote, and about 45% offer remote or hybrid work as of October 15, 2026. Migrate Mate shows the location on each listing.