Autonomy Perception Engineer — Real-Time Sensor Fusion

Capgemini; Northern (KY); Hybrid; USD 82,000 - 193,000; Full time

Benefits offered by this job

Benefits package

Job summary

Capgemini is seeking a Perception Engineer to lead the design and deployment of perception algorithms across autonomous platforms. You will architect real-time C++ processing pipelines and define sensor integration standards for LiDAR, radar, and camera data.

You will collaborate with planning and controls teams, deploy systems at customer sites, and mentor junior engineers while documenting architecture and decisions for team knowledge.

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or related field.
• 4–7 years of experience developing perception systems for autonomous vehicles or robotics.
• Expert proficiency in production-grade, multithreaded Linux C++.
• Experience with LiDAR/Radar/Camera or sensor fusion and object tracking.

Responsibilities

• Lead design, development, and deployment of perception algorithms for LiDAR, radar, camera, and sensor fusion.
• Architect real-time C++ processing pipelines for object detection, classification, tracking in embedded environments.
• Define sensor selection criteria and validation processes for perception systems.
• Collaborate cross-functionally with planning, controls, and systems engineers.
• Mentor junior engineers and conduct code reviews.

Skills

C++

ROS/ROS2

Sensor fusion

Python

Multithreading

Machine learning

Education

Bachelor's in CS/EE/Robotics

Master's degree preferred

Tools

DDS

Linux

Job description

Capgemini is seeking a Perception Engineer to lead the design and deployment of perception algorithms across autonomous platforms. You will architect real-time C++ processing pipelines and define sensor integration standards for LiDAR, radar, and camera data.

You will collaborate with planning and controls teams, deploy systems at customer sites, and mentor junior engineers while documenting architecture and decisions for team knowledge.