2 of 2 Batch Processing Jobs in Cambridgeshire

client, a fast-growing AI company based near Cambridge, is seeking a Senior RF Data Scientist/Research Engineer to work at the intersection of RF hardware, digital signal processing, and machine learning. This hands-on R&D role involves analysing complex RF datasets, developing advanced signal-processing pipelines, and contributing to cutting-edge UAV/drone detection … platforms (e.g., bladeRF, USRP) to extract, classify, and interpret RF signal features Building diagnostic RF analysis tools (timefrequency plots, cyclic spectra, EVM, autocorrelation, constellation tracking, etc.) Designing RF data-processing pipelines built around practical hardware constraints (bandwidth, ADC limits, gain stages, timing jitter) Modelling RF front-end behaviour (filters, mixers, LOs, AGC, noise figure) to improve signal integrity and … inference accuracy Developing ML and statistical models for RF classification, anomaly detection, and emitter identification Prototyping real-time or batch-processing systems in Python (NumPy, SciPy, PyTorch) with potential integration via ZMQ, GNU Radio, or C++ backends Leading RF data collection, field experiments, and over-the-air testing using drones, wireless devices, and custom transmitters Requirements Strong Python More ❯

client, a fast-growing AI company based near Cambridge, is seeking a Senior RF Data Scientist/Research Engineer to work at the intersection of RF hardware, digital signal processing, and machine learning. This hands-on R&D role involves analysing complex RF datasets, developing advanced signal-processing pipelines, and contributing to cutting-edge UAV/drone detection … e.g., bladeRF, USRP) to extract, classify, and interpret RF signal features Building diagnostic RF analysis tools (time–frequency plots, cyclic spectra, EVM, autocorrelation, constellation tracking, etc.) Designing RF data-processing pipelines built around practical hardware constraints (bandwidth, ADC limits, gain stages, timing jitter) Modelling RF front-end behaviour (filters, mixers, LOs, AGC, noise figure) to improve signal integrity and … inference accuracy Developing ML and statistical models for RF classification, anomaly detection, and emitter identification Prototyping real-time or batch-processing systems in Python (NumPy, SciPy, PyTorch) with potential integration via ZMQ, GNU Radio, or C++ backends Leading RF data collection, field experiments, and over-the-air testing using drones, wireless devices, and custom transmitters Requirements Strong Python More ❯