
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?
Despite our growth and scale, we're still just getting started. That's where you come in.
We're looking for a Senior/Staff Software Engineer, Search to improve the data and search systems behind Radar's geocoding platform. Our daily traffic is over 1 Billion API calls / day (15,000 requests / second), so you will be operating at scale. You'll improve the quality and coverage of our location data, build and automate the pipelines that keep it growing, and improve how we understand queries, retrieve candidates, and rank results across geocoding and autocomplete. You'll use ML and LLMs where they can materially improve these systems, from data enrichment and matching to query understanding and search relevance. This is a software engineering role first, you don't need a research background, but you should be excited to work across data, search, and backend systems and reach for ML when it's the right tool. This role will be based out of our NYC HQ.
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.
Our core backend service is HorizonDB, a geospatial database written in Rust that powers geocoding: forward and reverse geocoding, autocomplete, and address validation.
It's built on custom search indexes and stores like Tantivy, RocksDB, and FSTs, with ML models for query understanding and ranking.
Our geospatial data pipelines are written in Scala and Python on Airflow, merging commercial and open data sources into the indexes HorizonDB serves.
The API layer is a Node.js TypeScript app, and we use MongoDB, S3/Athena, and Redis.
Everything is deployed to AWS via Kubernetes on EKS using Terraform.
Most engineers are in the on-call rotation.
We sponsor OpenStreetMaps, MapLibre, and OpenAddresses.
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.
We’ll share full details of our benefits package at the offer stage. Benefits may vary by location.
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.

Radar is the world's first Location OS: next-gen geofencing and maps infrastructure for developers and AI-enabled solutions for marketing, fraud, and operations teams, all in a single platform. Hundreds of enterprises, including DICK'S Sporting Goods, T-Mobile, Inspire Brands, and bet365, use Radar to engage their customers, protect their business, and optimize their operations across hundreds of millions of devices worldwide.