Signal Processing / Machine Learning Engineer

Signal Processing / Machine Learning Engineer Do you want to work in a start-up innovative environment with advanced algorithm development at the intersection of radar, signal processing, simulation and machine learning? Radar Reticence is looking for a system-oriented algorithm developer who can combine mathematical depth with an understanding of how algorithms perform in real, complex systems. In this role, you will help develop, model and evaluate advanced algorithms for radar systems and translate functional needs, test data and physical constraints into robust algorithmic solutions. What you will work with Algorithm development, modelling and simulation for radar systems. Signal processing for complex sensor data and real-world radar measurements. MATLAB-based modelling, simulation and data analysis. Detection, filtering, spectral analysis, estimation and robustness evaluation. Combining classical signal processing with data-driven methods. Fusion with video data for extraction of annotation data. Analysis of test data from lab environments, vehicles and simulations. Evaluating algorithmic trade-offs between complexity, performance and computational capacity. Working closely with experts in radar, firmware, software and system architecture. We believe you have Are a MSc with some years of working experience or PhD Strong skills in algorithm development and mathematical modelling. Very good knowledge of MATLAB for modelling, simulation and data analysis. Skilled in ML tools, e.g. PyTorch and experiences with different ML methods, from standard U-nets to transformers. A solid foundation in digital signal processing. Understanding of electromagnetic wave propagation, noise, interference and signal integrity. Ability to analyze complex datasets and identify root causes of deviations. Strong analytical thinking and the ability to communicate technical trade-offs clearly. It is a plus if you have experience with Radar signal processing. Sensor fusion. Image processing/Computer Vision Deep learning. Automotive, ADAS or autonomous systems. Safety-critical or real-time development environments Required Fluent in English, both spoken and written. Able to make yourself understood in Swedish, both spoken and written. Able to work from one of our offices in Linköping or Halmstad at least a few days per week. Who you are You are analytical, curious and technically driven. You enjoy complex problems where there are no ready-made answers, and you are able to move between mathematical detail and system-level impact. You like working in cross-functional teams and can explain advanced technical concepts in a clear and constructive way. About Radar Reticence Radar Reticence develops next-generation radar technology for safer and more autonomous vehicles. Built on deep Swedish radar expertise and research from Halmstad University, our patented software-based solution makes automotive radar more robust against interference – one of the fastest-growing challenges in advanced driver assistance and autonomous mobility. We are now entering an exciting growth phase: moving from advanced research and validated testing toward chip integration, customer proof-of-concepts and commercial deployment with leading actors in the mobility and radar ecosystem. In 2026, Radar Reticence secured long-term financing through a new investment round and was awarded EIC Accelerator funding from the European Union. We are building the team that will take our technology from lab and prototype to the radar systems of future vehicles. Learn more about us at Next Generation Radar - Radar Reticence Avdelning LEAD Startups Locations Linköping Remote status Hybrid Linköping About LEAD LEAD is one of Sweden’s leading business incubators, helping entrepreneurs build companies faster and with greater confidence. We work with entrepreneurs whose companies are innovative and have the potential to scale. LEAD is owned by Linköping University and is funded by the municipalities of Norrköping and Linköping, as well as Vinnova. Applicant tracking system by Teamtailor