Principal Perception Architect, Detection and Fusion

Caterpillar

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Irving, TX
Salary
$147,760–$240,110 / yr
Posted
7 days ago
Freshness
Confirmed live yesterday
Closes
Oct 31, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $224k
This role $194k
$133k most similar roles pay here $290k

This role pays less than 73% of similar roles. Most pay $193,935–$254,750 — the shaded band above. At the midpoint, this role pays about $194k versus about $224k for comparable roles.

Based on 240 similar postings.

Employer

About Caterpillar

Caterpillar Inc. is the world''s largest manufacturer of construction and mining equipment, diesel and natural gas engines, industrial gas turbines, and diesel-electric locomotives. Industry: Heavy Equipment & Manufacturing

Caterpillar currently has 62 open roles on FindRole.

Listed pay typically runs $131,789–$192,710 across 61 roles with salary data.

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At a glance

TL;DR · Principal Perception Architect, Detection and Fusion

As a Principal Perception Architect - Detection and Fusion, you will join the team to own the architecture for modular perception machine learning, sensor fusion, object tracking, object persistence, and 3D mapping. You will be responsible for transforming synchronized sensor data into reliable outputs such as drivable area segmentation and local-to-global 3D maps for use in robotics and safety analysis. The role requires expertise in processing camera images, lidar point clouds, 4D radar point clouds, IMU data, GNSS data, and machine state inputs. You will design architectures for object detection, ground plane segmentation, and multi-machine object lifecycle management. This position addresses the complex challenge of construction autonomy by building intelligent systems that enable machines to perceive their environment and make informed decisions within dynamic jobsites using advanced perception algorithms and sensor fusion techniques.

What you'll do

  • Define modular machine learning architectures for camera-based object detection and drivable area understanding.
  • Develop sensor fusion architectures integrating camera, lidar, 4D radar, IMU, GNSS, and machine state data.
  • Design systems for object tracking, lifecycle management, and persistent representation across multiple machines.
  • Own the 3D mapping architecture including local scene representation and local-to-global map alignment.
  • Create structured perception output interfaces for robotics, simulation, world model creation, and safety analysis.
  • Transform raw synchronized sensor data into reliable outputs like detected objects and drivable area segmentation.
  • Collaborate with edge platform, robotics, and simulation teams to integrate algorithms into autonomy capabilities.

What we're looking for

  • Experience with modular perception machine learning and sensor fusion for autonomous vehicles and robotics.
  • Hands-on experience with camera images, lidar point clouds, 4D radar, IMU, GNSS, and machine state data.
  • Proficiency in object detection, drivable area understanding, ground plane segmentation, and 3D mapping.
  • Expertise in object tracking, persistence, association, and lifecycle management for multi-machine environments.
  • Ability to define perception output interfaces for robotics, simulation, and safety analysis.
  • Ability to work cross-functionally with edge platform, robotics, and simulation teams.
  • Familiarity with construction or off-road autonomy applications is preferred.

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