We are working with a high-growth AI technology company in the Greater Cambridge area who are seeking a Senior RF Data Scientist / Research Engineer to work at the intersection of RF hardware, digital signal processing, and machine learning. This is a hands-on R&D role ideally suited to engineers and scientists who enjoy fast-paced prototyping, complex problem-solving, and developing cutting-edge UAV/drone detection technologies.
In this role, you will analyse complex RF data from software-defined radios (SDRs), develop advanced signal-processing pipelines, and contribute directly to the design and testing of novel sensing systems. You will be responsible for extracting and classifying RF signal features from raw IQ data, building diagnostic tools to characterise RF signals, and designing data-processing pipelines that account for real-world hardware constraints such as bandwidth limitations, ADC performance, and timing jitter. You will also model RF front-end behaviour, improving signal integrity and inference accuracy, and apply machine learning and statistical models for classification, anomaly detection, and emitter identification.
You will prototype real-time and batch-processing systems using Python (NumPy, SciPy, PyTorch) and integrate them with frameworks such as GNU Radio, ZMQ, or C++ backends. The role involves leading RF data collection, field experiments, and over-the-air testing with drones, wireless devices, and custom transmitters. Collaboration across engineering and research teams is central, and you will contribute to both experimental design and iterative R&D development.
The ideal candidate will have strong Python proficiency for data analysis and prototyping, a solid understanding of digital signal processing (FFT, filtering, modulation, correlation, resampling, and noise modelling), and familiarity with SDR frameworks such as GNU Radio, SDRangel, osmoSDR, or SoapySDR. A practical understanding of RF hardware chains - from antenna through filters, mixers, and ADCs - and their impact on baseband data is essential. You should also be comfortable debugging SDR setups, performing field-based RF data collection, and analysing wireless protocols such as Wi-Fi, LTE, and LoRa. Strong communication skills and the ability to work iteratively in a research-focused environment are essential.
Experience with SDR hardware (bladeRF, HackRF, USRP, PlutoSDR), RF lab equipment (spectrum analysers, VNAs, signal generators), embedded or real-time systems, beamforming, passive radar, or antenna array design is highly desirable. Knowledge of RF circuit fundamentals, FPGA or GPU acceleration, and prior publications, patents, or open-source RF/ML contributions are also beneficial but not essential.
This is a full-time role based in Saffron Walden / Greater Cambridge, with flexibility for onsite or hybrid working depending on project needs. You will join a dynamic Research & Prototyping team, directly influencing early-stage hardware-software product development and shaping the next generation of AI-driven sensing technologies.
If you are an experienced RF data scientist or research engineer looking for a hands-on role at the cutting edge of RF, signal processing, and machine learning, we would love to hear from you.
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