Requirements

• PhD or equivalent research experience in ML, signal processing, physics, electrical engineering, or related fields with publications in reputable venues such as NeurIPS, ICLR, ICML, or ICASSP.
• Experience deploying non-trivial machine learning models in real products, understanding the challenges from research to deployment.
• Comfort with irregular, noisy sequence data using temporal models, self-supervised or contrastive methods, and calibration under distribution shifts.
• Proficiency in writing clean Python code and willingness to learn Rust for deployment needs.
• Ability to read, reimplement, and critically evaluate research papers and their results.
• Strong communication skills to explain research to ML peers, RF engineers, and end users.

Nice to haves

• Experience with electronic warfare (EW), signals intelligence (SIGINT), electronic support measures (ESM/ELINT), radar warning receivers (RWR), or radar concepts.
• Familiarity with RF signal theory sufficient to collaborate effectively with RF engineers, including modulation, propagation, and antenna patterns.
• Experience deploying ML models to edge or embedded hardware using ONNX, TensorRT, quantisation, or profiling on constrained GPUs.

What you'll be doing

• Working on machine learning and signal processing for RF data to build AI capabilities in electronic warfare systems.
• Developing models that detect, classify, and analyze RF signals in complex, contested spectral environments.
• Handling messy, irregular, and adversarial data with strict latency and compute constraints.
• Owning problems end-to-end: from literature review and prototyping on recorded data to deployment and monitoring in real platforms.
• Collaborating closely with a small research team, RF and hardware engineers, and system operators.
• Focusing on areas like self-supervised representation learning, deinterleaving, emitter identification, mode recognition, and anomaly detection on embedded hardware.

Perks and benefits

• Competitive salary and VSOP options.
• Relocation support up to €2,500 plus 4 weeks of temporary accommodation.
• Annual learning allowance of €500/£450.
• Health and wellness support including gym membership and mental health services (Nilo.health).
• Regular company events and monthly social allowances.
• Enhanced parental leave: 22 weeks fully paid for primary caregivers and 6 weeks for secondary caregivers.
• Family support including 5 days paid family emergency leave, 100% remote work option during pregnancy, and phased return to work.