Signal Processing & Sensor Fusion Engineer
UK-based (hybrid/remote).
Periodic on-site attendance in Liverpool and at external locations
A Signal Processing & Sensor Fusion Engineer is required for integration, testing, and field trials, in accordance with project needs.
About Voyant
Voyant is a disruptive spinout from the University of Liverpool providing advanced tracking, sensor fusion, and alternative navigation solutions for defence and autonomous platforms. It uses proprietary technology based around particle filters to enhance sensors, data fusion and also alternative navigation across all domains – land, air, sea and space.
About the role
We are seeking a highly capable engineer to develop advanced algorithms and software for signal processing, tracking, and multi-sensor data fusion.
You will work on real-world sensing challenges involving noisy, asynchronous, and multi- modal data, contributing to systems deployed in complex operational environments.
This role is ideal for someone who enjoys combining mathematical rigour with practical engineering, and wants to see their work transition from research into real-world capability.
What you’ll do
- Design and implement algorithms for:
– Signal processing and detection
– Target tracking and state estimation
– Multi-sensor data fusion - Develop robust, efficient software in Python and C++
- Work with real-world sensor data (e.g. acoustic, sonar, radar, EO/IR)
- Build and evaluate tracking systems in simulation and live environments
- Contribute to the development of reliable, verifiable systems suitable for deployment in safety-critical environments
- Analyse performance and iterate on algorithm design
Required skills & experience
- Strong background in one or more of:
– Signal processing
– Statistical estimation / Bayesian methods
– Applied mathematics, physics, or engineering - Strong ability to understand and implement algorithms from scientific literature
- Experience implementing sequential Bayesian inference methods for state estimation and tracking (e.g. Kalman filters, particle filters, or related probabilistic approaches)
- Experience working with real-world sensor systems and data (e.g. sonar, radar, acoustic, or vision), including noisy, asynchronous, or imperfect measurements
- Strong programming skills in Python (NumPy, SciPy, etc.) and/or C++ (for performance-critical components)
- Experience writing clean, testable, and maintainable code
Desirable experience
- Multi-target tracking and data association (e.g. JIPDA, MHT trackers)
- Experience developing software for safety-critical or high-integrity systems
- Experience with tracking or sensor fusion frameworks (e.g. Stone Soup)
- Experience handling real-world sensing challenges, including::
– out-of-sequence measurements (OOSM)
– sensor uncertainty and latency - Experience with simulation, modelling, or digital twin environments
- Experience applying machine learning to time-series or signal data
Background
- MSc, PhD, or equivalent experience in a relevant discipline
- Candidates from:
– Defence sector
– Academia (post-docs encouraged)
– Commercial software or deep-tech environments
Security
- UK national preferred
- Must be eligible for SC clearance (existing clearance not required)
Why Join
- Work on technically challenging, real-world sensing problems
- Take algorithms from concept to deployment
- Enjoy a high level of autonomy and technical ownership
- Flexible hybrid/ remote working