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We are building a next-generation tracking and motion inference platform that can understand real-world movement patterns — even in GNSS-degraded environments.
As our Sensor Fusion Engineer, you will be at the core of this innovation, designing the backbone algorithms that synchronize, filter, and fuse sensor data (IMU, magnetometer, barometer, GNSS) into robust, physics-aware motion signals that our backend ML engine can learn from.
You will collaborate with researchers, ML engineers, and product teams to push the boundaries of real-world motion understanding and enable applications across robotics, AR/VR, navigation, and smart mobility.
Design and implement sensor fusion algorithms to combine data from multiple sensors (IMU, magnetometer, barometer, GNSS).
Develop robust, physics-aware filtering frameworks (e.g., Kalman, complementary, or particle filters) for accurate motion estimation.
Optimize sensor data pipelines for real-time processing, synchronization, and noise reduction.
Integrate motion inference algorithms into production systems and validate them using real-world datasets.
Collaborate with ML and backend teams to build hybrid (physics + ML) models for advanced motion analytics.
Contribute to simulation and validation tools using ROS or motion-capture systems.
Research and apply state-of-the-art methods in inertial navigation, signal processing, and localization.
3–7 years of professional experience in sensor fusion, navigation, or motion tracking (robotics, UAVs, AR/VR).
Strong understanding of kinematics, inertial navigation, and coordinate transformations.
Hands-on experience with Kalman and complementary filters and signal processing techniques.
Proficiency in Python and/or C++, with strong knowledge of scientific libraries such as NumPy, SciPy, and Eigen.
Familiarity with GNSS positioning and barometric altitude estimation.
Strong analytical, problem-solving, and debugging skills.
Exposure to ML-aided sensor fusion or hybrid (physics + ML) modeling.
Experience with ROS, motion-capture tools, or real-world dataset validation.
Knowledge of real-time systems, embedded platforms, or robotics frameworks.
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Marcus Rivera
Chief Revenue Officer
Tenengroup Ltd.
Tempus
LocalEyes Ltd.
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