Multimodal Sensing and Fusion Engineer

Who we are

Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards. 

As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously. 

We are an ambitious and committed team of engineers, AI specialists and customer-facing programme managers. We are looking for mission-driven people to join our European teams – and apply their skills to solve the most complex and impactful problems. We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications. 

The role

Helsing builds software and AI that makes existing defence hardware up to ten times more capable. The sensing stack is where that capability begins. Without precise, synchronised, calibrated sensor data, the AI has nothing to work with. 

As Multimodal Sensing and Fusion Engineer, you will own that stack end to end. You will architect the multimodal perception front-end that combines electro-optical and long-wave infrared cameras, radar, LiDAR, and inertial sensing into a single, coherent input to Helsing's AI. You will translate mission requirements into concrete specifications for sensor selection, placement, synchronisation, and calibration, and you will define the safety concepts that ensure the system degrades gracefully and fails safe in the field. 

This is not a prototyping role. The systems you design go into operational environments. The quality of the data you deliver directly affects the decisions Helsing's AI supports in the field. You will sit at the intersection of hardware engineers, electrical engineers, and AI and computer-vision researchers, working out of Munich, Berlin or London. 

The day-to-day

• Define the multimodal sensing architecture: select and integrate EO and LWIR cameras, radar, LiDAR, and IMUs, aligning requirements with the AI team to optimise algorithm performance and balance trade-offs across size, weight, power, cost, and robustness. 

• Own sensor synchronisation: design and implement time synchronisation across heterogeneous sensors using PTP/gPTP, PPS, and hardware triggers such as Hsync and Vsync, so all modalities share a common, precise time base. 

• Own sensor calibration: develop intrinsic, extrinsic, spatial, and temporal calibration procedures, including online and continuous recalibration, across cameras, radar, and IMU.