Job Description:
About us, we're a global leader in bridging the physical and digital worlds to enable breakthroughs at the Intelligent Edge.
We combine analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world.
Our team is on a mission to redefine how machines perceive and interact with the world. We're building real-time, intelligent systems that combine world-class sensor technology with cutting-edge AI — at the Edge, where milliseconds matter.
Key Responsibilities:
* Design, prototype, and deploy algorithms for SLAM, visual odometry, and multi-sensor fusion in robotics and edge computing applications.
* Develop AI-driven methods for mapping, pose estimation, localization, and semantic perception, with an emphasis on performance and generalization.
* Train and evaluate deep learning models for spatial understanding, integrating with classical perception pipelines when needed.
* Work with real-world and simulated sensor data to test and refine models; contribute to internal datasets and benchmarking tools.
* Collaborate with embedded, systems, and software teams to bring perception solutions to production on resource-constrained edge platforms.
Qualifications:
* 6+ years of experience in AI, robotics, or computer vision, including 4+ years focused on SLAM, sensor fusion, or perception systems.
* Bachelor's degree in a relevant field (e.g., Robotics, Computer Science, Electrical Engineering); M.S. or Ph.D. preferred.
* Strong understanding of 3D geometry, motion estimation, sensor fusion, and real-time system design.
* Hands-on experience building and deploying SLAM or VIO systems (e.g., ORB-SLAM, RTAB-Map, DSO, OpenVINS, Cartographer).
* Proficient in Python and C++, with practical experience using PyTorch, TensorFlow, or ROS.
* Comfortable working with real-world sensor data (e.g., stereo cameras, LiDAR, IMU) and simulation tools like Gazebo, Isaac Sim, or Unreal.
* Experience with DevOps/MLOps tools: Docker, CI/CD pipelines, cloud platforms (Azure, AWS), version control (Git).
* Skilled at communicating technical insights, collaborating with multi-disciplinary teams, and contributing to shared architectural decisions.
Why Join Us?
Join our team to help create truly intelligent edge systems — where sensing, learning, and acting happen in real time. You'll work in a fast-paced, collaborative environment, solving hard problems with people who care about impact, reliability, and real-world performance.