Senior Perception Engineer — Remote ADAS & Sensor Fusion

LM Wind Power / GE; Novi (MI); Hybrid; USD 110,000 - 160,000; Full time

Job summary

Stoneridge in Novi, MI seeks a Senior Perception Engineer to advance perception systems for commercial vehicles. You will integrate camera, radar, LiDAR and ultrasonic inputs, and drive algorithms from prototyping through deployment, with focus on safety standards and robust real-time performance.

The role requires a Master’s degree and 3+ years in robotics, EE, CS, or mechanical engineering, with hands-on expertise in embedded software, ML frameworks, and ISO safety/cybersecurity standards.

Qualifications

• Master's degree in a relevant field plus 3 years of experience.
• 3 years of experience with C, C++, Python; embedded software and ADAS.
• Telecommuting is permitted; 20% domestic travel across the U.S.

Responsibilities

• Architect conceptual designs for commercial vehicle perception systems with cross-functional teams.
• Design and optimize multimodal ADAS features using camera, radar, LiDAR, and ultrasonic sensors.
• Develop, deploy, and debug real-time embedded software on ARM Cortex, NVIDIA Jetson, TI Jacinto.
• Configure and optimize RTOS, vendor SDKs, and IDEs for fault-tolerant sensor-based systems.
• Implement and benchmark computer vision algorithms using OpenCV/OpenVX and Vulkan.
• Accelerate deep neural network inference with TensorRT/ONNX for real-time performance.
• Engineer full lifecycle of sensor integration including calibration and ISP tuning.
• Contribute to software compliant with ISO26262 and ISO/SAE21434 within an Agile workflow.
• Author documentation, validation reports, and calibration procedures; lead technical reviews.

Skills

C/C++ programming

Python

Embedded software

Sensor fusion

Computer vision

OpenCV/OpenVX

TensorRT/ONNX

ADAS components

Education

Master's degree in Robotics/EE/CS/ME

Tools

Git

JIRA

CI/CD

Job description

Stoneridge in Novi, MI seeks a Senior Perception Engineer to advance perception systems for commercial vehicles. You will integrate camera, radar, LiDAR and ultrasonic inputs, and drive algorithms from prototyping through deployment, with focus on safety standards and robust real-time performance.

The role requires a Master’s degree and 3+ years in robotics, EE, CS, or mechanical engineering, with hands-on expertise in embedded software, ML frameworks, and ISO safety/cybersecurity standards.