**THE OPPORTUNITY**
You will be our first hire in Spain and a foundational member of the team. This is a rare chance to own critical models end-to-end, influence the technical roadmap from day one, and grow rapidly alongside a world-class engineering organisation.
You will develop physics-grounded EM/RF models — link budgets, signal analytics, interference analysis — and couple them with machine-learning approaches that improve the reliability, efficiency, and intelligence of space data transport.
**WHAT YOU WILL DO**
- Build and validate EM/RF models covering link budgets, propagation effects, SNR/BER, modulation and coding impacts, interference and jamming considerations, spectral efficiency, and performance margins.
- Develop signal-analysis tooling and data pipelines to extract actionable features from RF telemetry and ground-station data.
- Couple physics-based models with ML approaches — predictive performance modelling, anomaly detection, link-quality estimation, and adaptive scheduling inputs.
- Translate complex real-world constraints into clean, maintainable models with clear, actionable outputs for our platform.
- Collaborate closely with the CTO and engineering team to integrate models into production product workflows.
- Own deliverables end-to-end with strong autonomy: design → implementation → testing → documentation.
**WHAT WE ARE LOOKING FOR**
- Outstanding academic record in Aerospace Engineering, Telecommunications, Electrical Engineering, Physics, or a closely related discipline.
- 1-2 years of relevant experience (internships and research experience count) in RF, communications, signal processing, space systems, or telecoms.
- Strong theoretical foundations in electromagnetics and communications: link budgets, noise analysis, interference modelling, filtering, and detection/estimation theory.
- Proficiency in Python (scientific stack: NumPy, SciPy, Pandas, Matplotlib) and hands-on experience with model prototyping; familiarity with MATLAB, GNU Radio, or similar tools is a bonus.
- Genuine curiosity about machine learning and the ability to bridge physics-driven modelling with data-driven approaches — ML expertise on day one is not required.
- Highly proactive and self-directed: you can work independently, take initiative, and communicate clearly in a fast-moving, distributed team.
**WHY JOIN US**
- Silicon Valley learning curve — direct exposure to how elite teams build, iterate, and scale deep-tech products.
- Founding hire in Spain — outsized ownership, real strategic impact, and rapid professional growth from day one.
- Work from the ESA BIC / Aeropuerto de Castellón ecosystem — a thriving deep-tech environment with a strong space community.
- Competitive salary plus equity participation — we want builders who think long-term and share in the upside they create.
- Direct mentorship from the CTO and close collaboration with the full core team across continents.
**HOW TO APPLY**
Send your CV together with a short cover note of 5-10 lines addressing the following two points:
- A model, project, or paper you are proud of — briefly describe what it is, what problem it solved, and what you learned.
- Why you want to work at the intersection of RF/EM physics and machine learning for space connectivity.
Tipo de puesto: Jornada completa
Ventajas:
- Flexibilidad horaria
- Ordenador de empresa
- Programa de formación
- Teletrabajo opcional
Ubicación del trabajo: Teletrabajo híbrido en 12181 Benlloch, Castellón provincia