Physical AI Engineer

We are looking for a Physical AI Engineer

We are looking for a Physical AI Engineer with deep technical expertise in perception systems, object detection, and semantic understanding. You will drive the development of robust, real-time machine learning models for integration into smart, physical products. Your work will directly contribute to creating autonomous systems that operate reliably in dynamic real-world settings, specifically within home environments, adapting to the unique and ever-changing conditions found at home.

Your Responsibilities

• Design, development, and deployment of perception algorithms (object detection, semantic segmentation, tracking) for real-world applications.
• Build and test robotic prototypes by leveraging rapid prototyping tools.
• Deploy and validate scalable AI-driven control algorithms on embedded hardware platforms, ensuring robust and intelligent operation of robotic systems in real-world environments.
• Integrate AI models with hardware platforms using sensor data (e.g., image, LiDAR, IMU).
• Drive applied research in physical AI and computer vision, staying on top of the latest developments.
• Collaborate across teams (AI, robotics, embedded systems) to ensure seamless integration.
• Support data acquisition and annotation strategies to improve model robustness and generalization.
• Occasionally participate in hardware-in-the-loop testing, validation environments, and field deployments.
• Contribute to building technical excellence in the team.

Your Qualifications

• Master's or PhD in Computer Science, Robotics, Electrical Engineering, or related field.
• 5+ years of experience in developing and deploying AI/perception systems, ideally in robotics or smart devices.
• Deep knowledge of deep learning for computer vision (object detection, semantic segmentation, SLAM).
• Strong experience with PyTorch and/or TensorFlow, including deployment on edge devices.
• Proficient in C++ and Python in Linux environments.
• Solid understanding of sensor technologies (camera, LiDAR, radar) and data fusion.
• Familiarity with frameworks like ROS 2, OpenCV, Open3D, PCL, and Nvidia SDKs.
• Ability to work independently in R&D-heavy, fast-paced environments.

Nice to Have

• Experience with Nvidia Jetson platforms, TensorRT, or CUDA.
• Exposure to Rust programming for low-level robotics or embedded AI applications.
• Experience in real-time system constraints and model optimization (quantization, pruning).