Job Description

ARQUIMEA, is a technology company operating on a global scale, providing innovative solutions and products in highly demanding sectors.

Our areas of activity include Aerospace, Defense and Security, Big Science, Biotechnology, and Fintech.

Estimation, Tracking and Real-Time Systems

We are looking for a highly skilled Digital Signal Processing Engineer to join our R&D team and contribute to the design, implementation, and validation of advanced algorithms for high-performance sensing and real-time systems.

This position is intended for engineers with a strong background in digital signal processing, estimation theory, and algorithm development, capable of contributing across multiple technological domains and projects. Particular value will be placed on candidates with experience in multi-sensor data fusion, Bayesian estimation and tracking, and the deployment of algorithms on embedded real-time platforms Experience in inertial navigation systems (INS), attitude and heading reference systems (AHRS), or high-precision pointing systems will be considered a strong plus.

Key responsibilities

• Design, develop, and validate advanced signal processing, estimation, tracking, and sensor fusion algorithms for real-time applications.

• Contribute to the development of DSP functions such as filtering, spectral analysis, estimation, modulation/demodulation, non-linearity compensation, and noise reduction, depending on project requirements.

• Develop Bayesian filtering, recursive estimation, and multi-sensor data fusion algorithms for demanding sensing and control applications.

• Formulate and analyse dynamic and measurement models, including uncertainty propagation and performance-limiting error sources.

• Build and maintain numerical models and simulation environments in MATLAB/Simulink, Python, and C/C++ to support algorithm design, trade-off analysis, and performance validation.

• Define and use quantitative performance metrics to assess algorithm accuracy, robustness, stability, consistency, and computational efficiency.

• Characterize algorithm performance through simulation, prototyping, laboratory testing, and field validation under representative operational conditions.

• Collaborate closely with embedded software, FPGA, and system engineering teams to integrate algorithms into real-time target platforms

• Support the transition from concept and feasibility studies to implementation, verification, and prototype deployment

• Work in a multidisciplinary R&D environment, coordinating technical activities with product and project teams to ensure objectives, milestones, and deliverables are met.

• Required technical expertise

• Strong theoretical and practical background in digital signal processing, statistical estimation, and Bayesian inference

• Proven experience in the design and development of signal processing and estimation algorithms for real-time systems.

• Hands-on experience with Kalman-filter-based estimation frameworks, including linear and nonlinear formulations such as EKF, UKF, or related approaches.

• Experience in state-space modelling, stochastic processes, uncertainty propagation, and estimator performance evaluation.

• Solid understanding of noise characterization, spectral analysis, stochastic error modelling, and time/frequency-domain analysis.

• Strong capability to translate algorithms from high-level modelling environments into embedded real-time implementations, considering latency, memory, throughput, numerical precision, and computational constraints

• Experience in verification and validation of algorithms using simulation-based methods, real datasets, and experimental campaigns.

• Strong programming and modelling skills in MATLAB/Simulink, Python, and C/C++

• Working knowledge of digital implementation constraints, sensor interfaces, timing/synchronization, and collaboration with FPGA/SoC-based platforms

Required qualifications and experience

• Bachelor’s degree in electrical engineering, Electronics Engineering, Telecommunications Engineering, Computer Engineering, or a related discipline.

• Master’s degree in a relevant field is required.

• PhD in signal processing, estimation, control, navigation, or a related area is highly valued.

• 5+ years of hands-on experience in R&D roles involving signal processing, estimation, tracking, sensor fusion, or real-time algorithm development.

• Proven experience in the development of advanced algorithms for embedded or real-time systems

• Experience working in multidisciplinary engineering environments involving software, hardware, and system-level integration.

Additional valued experience

• Experience in multi-sensor data fusion for navigation, orientation, tracking, or related applications.

• Experience with INS, AHRS, or other navigation/orientation systems.

• Familiarity with IMU and inertial sensor error modelling, calibration, alignment, and performance Characterization.

• Experience in high-precision pointing, stabilization, or orientation control systems

• Experience with GNSS/INS integration or other aided-estimation architectures.

• Familiarity with Monte Carlo analysis, requirement-driven verification, and hardware-in-the-loop or software-in-the-loop validation approaches.

• Knowledge of fixed-point implementation issues, real-time optimization, and performance tuning for embedded targets.

Soft skills

• Strong analytical and problem-solving skills.

• Ability to work effectively in collaborative, cross-functional, and multidisciplinary teams

• Strong technical communication, reporting, and documentation skills.

• Structured, proactive, and results-oriented approach to engineering work.

• Fluency in English and Spanish

• Eligible to work in the EU

Job opening in Madrid, las palmas de Gran Canarias, or Laguna en Tenerife.

Think Big, Do the Job & Enjoy Life

At ARQUIMEA, we value diversity and inclusion. We do not discriminate on the basis of race, color, religion, gender, sexual orientation, gender identity, nationality, age, disability, or any other legally protected characteristics. All candidates will be considered on equal terms based on their skills and experience.