Senior AI/ML Robotics Engineer - Edge Perception & SLAM

Analog Devices; Munster; On-site; EUR 120,000 - 180,000; Full time

Job summary

Analog Devices’ Edge AI group seeks a Staff AI/ML Engineer with strong perception, SLAM, and sensor-fusion background to build real-time, edge AI systems for robots and sensors. You’ll localize, map, and understand environments, enabling robots to operate in dynamic settings.

You’ll work alongside hardware, embedded, and software experts, contributing to robust perception pipelines and production-grade implementations at the edge.

Qualifications

• 6+ years in AI, robotics, or computer vision with 4+ years in SLAM, sensor fusion, or perception.
• Bachelor’s in Robotics/CS/EE; MS/PhD preferred.
• Strong 3D geometry, motion estimation, sensor fusion, real-time design.

Responsibilities

• Design, prototype, deploy SLAM, visual odometry, and multi-sensor fusion.
• Develop AI-based mapping, pose estimation, localization, and semantic perception.
• Train/evaluate deep learning models for spatial understanding with real data.
• Work with real-world and simulated sensor data to refine models.
• Collaborate with embedded, systems, and software teams to productionize on edge devices.
• Engage in code reviews, planning, and architecture decisions; own tech areas.
• Stay current with AI robotics trends and integrate relevant advances.

Skills

SLAM

Sensor fusion

Perception systems

Python

C++

ROS

3D geometry

Real-time systems

Deep learning

PyTorch

TensorFlow

Education

Bachelor’s degree in Robotics/CS/EE

MS or Ph.D. preferred

Tools

Gazebo

Isaac Sim

Unreal

Docker

CI/CD

Azure

AWS

Git

ROS

Job description

Analog Devices’ Edge AI group seeks a Staff AI/ML Engineer with strong perception, SLAM, and sensor-fusion background to build real-time, edge AI systems for robots and sensors. You’ll localize, map, and understand environments, enabling robots to operate in dynamic settings.

You’ll work alongside hardware, embedded, and software experts, contributing to robust perception pipelines and production-grade implementations at the edge.