Principal AI/ ML Robotics Engineer - Environmental Perception

About the position Responsibilities • Lead the design and deployment of SLAM, VIO, and multi-sensor fusion systems that enable robust, real-time mapping and localization across diverse environments. • Drive algorithm development and evaluation for perception tasks, including pose estimation, depth reconstruction, loop closure, map optimization, and semantic understanding. • Architect AI pipelines that combine classical and learned methods (e.g., CNNs, transformers, foundation models) for environmental understanding at the edge. • Develop real-world and simulation-based datasets for benchmarking and validation; guide sensor selection and system integration. • Collaborate cross-functionally with embedded, hardware, and systems engineers to bring scalable solutions from research to production. • Stay current with the state of the art in robotics, SLAM, Edge AI, and self-supervised learning - and guide the team in adopting innovative technologies. • Contribute to the broader AI platform architecture, CI/CD pipelines, and MLOps practices. Requirements • 10+ years of experience in robotics, computer vision, or AI, including 5+ years in SLAM, VO, or sensor fusion; with 3+ years in a technical leadership role. • M.S. or Ph.D. in Robotics, Computer Science, Electrical Engineering, or related field. • Demonstrated expertise in at least one of the following: Visual-inertial odometry (VIO), Multi-sensor fusion (camera, LiDAR, IMU, encoders), 3D SLAM and mapping in dynamic environments, AI-based perception models for real-time localization. • Proven track record of deploying perception algorithms in real-world systems (e.g., autonomous robots, drones, AR/VR, self-driving platforms). • Strong programming skills in Python and C++, with experience in frameworks like PyTorch, ROS, g2o, or Ceres. • Comfortable working with real-time systems, embedded platforms, or simulators such as Gazebo, Isaac Sim, or Unreal Engine. • Familiar with MLOps and software best practices: CI/CD, containerization (Docker), orchestration (Kubernetes), etc. • Excellent communicator and collaborator - capable of leading multi-disciplinary teams and influencing stakeholders across hardware, software, and business domains. Nice-to-haves • Experience with self-supervised learning, foundation models for robotics, or transformer-based perception architectures. • Familiarity with industrial domains: factory automation, AMRs, predictive maintenance, etc. • Prior contributions to open-source projects (e.g., OpenVINS, ORB-SLAM3, DROID-SLAM, RTAB-Map, Cartographer). • Understanding of sensor design, signal processing, or embedded AI hardware platforms. Benefits • Join us in shaping the future of edge intelligence - where your work bridges the gap between sensing and understanding, and where you'll help machines not just gather data, but act meaningfully in the world.