Hivemapper17mo ago
Staff Software Engineer - Map AI Platform
Data ScienceDevOps & InfrastructureSoftware EngineerSoftware Engineering
6 views0 saves0 applied
Quick Summary
Overview
Hivemapper is a decentralized global map data network built by 10s of thousands of mapping devices. High-res sensors like RGB, Stereo Depth, GNSS, IMU, etc. feed sensor fusion and ML models at the edge. Data is automatically uploaded in near realtime over LTE or WiFi.
Technical Tools
distributed-systemsetlmentoring
Hivemapper is a decentralized global map data network built by 10s of thousands of mapping devices. High-res sensors like RGB, Stereo Depth, GNSS, IMU, etc. feed sensor fusion and ML models at the edge. Data is automatically uploaded in near realtime over LTE or WiFi. Enterprise tech, mapping, auto, robotaxis, rideshare, and entertainment represent some of the customers consuming data today.
APIs allow anyone to consume precisely extracted Map Features, HD map data, high-res street-level imagery, construction, and driving events for AV simulation. Tech-savvy customers develop and deploy software directly to our dashcams to get realtime data for things like change detection or visual semantic data mining. AI Fleet management tools drive value to large fleets of vehicles.
Map AI Platform
Every day, we process data from millions of KM from 10s of thousands of high resolution sensors deployed around the world. A symphony of different Sensor Fusion, ML, AI, 3D Reconstruction processes are performed at the edge and in our processing clusters, for which the Map AI Platform orchestrates.
The Map AI Platform is the core data engine that powers our data customers, consumer products, and user-facing AI technology. These complex systems control and learn patterns about map data all over the world and enable us to to continuously evolve map data intelligence, semantic extraction, QA at scale. For example, we’ve recently been using the system to learn hyperlocalized road network patterns to automatically QA and correct noise from map conflation.
We strongly believe in engineering design principles around abstraction and programmability that allow us to move quickly with minimal manual interventions. Our work is fast-paced, collaborative, and data-driven.
Location & Eligibility
Where is the job
San Francisco, United States
On-site at the office
Who can apply
US
Listed under
United States
Listing Details
- Posted
- February 24, 2025
- First seen
- March 26, 2026
- Last seen
- July 23, 2026
Posting Health
- Days active
- 119
- Repost count
- 0
- Trust Level
- 23%
- Scored at
- July 23, 2026
Signal breakdown
freshnesssource trustcontent trustemployer trust
External application · ~5 min on Hivemapper's site
Please let Hivemapper know you found this job on Jobera.
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