Imagine building the mathematical brain behind next-generation autonomous flight systems. As Lead Digital Signal Processing Engineer, you will drive the core algorithms powering advanced inertial measurement technologies that operate in demanding aerospace environments. Your work will directly shape the precision, stability, and intelligence of flight systems.
At Destinus, we are revolutionizing the defense industry with cutting-edge Unmanned Aerial Vehicles (UAVs), designed to meet the unique demands of modern defense operations and deliver speed, precision, and cost effectiveness. Destinus partners with government agencies and defense organizations worldwide to provide advanced solutions for mission-critical operations, enabling a new era of efficiency and technological superiority.
Tasks
- Lead the development of the mathematical architecture behind in-house inertial measurement unit technology.
- Build and maintain advanced digital twin models to simulate and optimize sensor behavior and system performance.
- Design and implement high-speed control loop algorithms for real-time embedded applications.
- Develop Extended Kalman Filters and sensor fusion algorithms in C++ to improve navigation accuracy and flight stability.
- Integrate AI-driven approaches for noise reduction, thermal compensation, and intelligent signal optimization.
- Analyze raw sensor data to validate performance, establish ground truth benchmarks, and continuously improve system accuracy.
- Collaborate closely with hardware, FPGA, embedded software, AI, and flight control teams to bridge the gap between theory and real-world aerospace applications.
- Contribute to the evolution of next-generation autonomous navigation and guidance systems across the Destinus platform.
Requirements
- M.Sc. or Ph.D. in Electrical Engineering, Robotics, Control Systems, Mathematics, Physics, or a related technical field.
- Expert-level proficiency in C++ for real-time embedded systems and RTOS environments.
- Strong experience with Python, MATLAB, or Simulink for modelling, simulation, and algorithm development.
- Deep understanding of digital signal processing, control theory, and sensor fusion principles.
- Experience working with inertial navigation systems and familiarity with gyro bias stability, random walk, and scale factor linearity.
- Solid understanding of embedded hardware systems, including high-speed SoCs and FPGA-to-ARM processor interfaces.
- Experience developing robust algorithms for high-performance aerospace, robotics, automotive, or defense applications.
- Strong analytical mindset with the ability to transform complex physical systems into scalable mathematical solutions.
- Enjoy solving deeply technical problems at the intersection of physics, software, and real-world engineering.
- Thrive in fast-moving environments where experimentation and innovation happen daily.
- Combine scientific rigor with hands-on execution and know how to turn theoretical models into systems that perform reliably in the field.
- Collaborative, curious, and motivated by building technology that pushes the boundaries of autonomous flight and aerospace intelligence.
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Über uns
Das Team
Collaborate closely with hardware, FPGA, embedded software, AI, and flight control teams to bridge the gap between theory and real-world aerospace applications.