Digital Signal Processing Engineer

About the role

Join Destinus to develop algorithms for a precision inertial sensor that relies on a mechanically resonant element. You will own the mathematical models, control loops, and signal‑processing algorithms that turn raw sensor data into accurate rate measurements.

Key responsibilities

• Design and simulate control loops (PLL, AGC, quadrature nulling) and define loop parameters such as bandwidth, gains, and stability margins.
• Develop outer‑loop algorithms for bias estimation, thermal compensation, and state estimation, preferably in maintainable C/C++ for embedded targets.
• Implement Kalman filtering approaches to convert the locked sensor output into usable measurements.
• Build and maintain co‑simulation environments and physics‑based models in Python or MATLAB to validate designs.
• Characterise sensor performance using Allan variance, bias instability, angular random walk, and related metrics.

Required profile

• Degree (B.Sc., M.Sc. or PhD) in Computer Science, Applied Mathematics, Applied Physics, Control Theory, Electrical Engineering or a related field.
• Strong foundation in control theory and digital signal processing, with practical experience in state estimation and Kalman filtering.
• Proficiency in Python or MATLAB for modelling, simulation and data analysis.
• Ability to translate physical behaviour into clear mathematical models and scalable algorithms.
• Experience writing maintainable C/C++ for embedded targets is strongly preferred.

Required skills

• Python
• MATLAB
• C / C++ (embedded)
• Control theory
• Digital signal processing
• Kalman filtering
• Embedded development