Signal Processing Engineer (Radar)

Signal Processing Engineer (RF Processing & Analytics)·Parismid

In short

→Ingeniero de procesamiento de señales radares en París, desarrollando algoritmos para imágenes de radar y detección de objetivos móviles en tiempo real.
→Trabajas desde investigación hasta validación en vuelo, con autonomía y sin supervisión directa, integrando con sistemas de EW y navegación sin GPS.
→Destacado: Trabajarás en un sistema de radar aéreo de alto impacto con pruebas reales en vuelo y en cámara anecoica.

El puesto requiere inglés para comunicación técnica y colaboración internacional.

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The questions they'll ask you

1. Describe cómo implementarías un algoritmo ISAR en tiempo real con restricciones de recursos en un sistema embebido.

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💵 USD · Remote · No visa

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What they ask for

✓2 a 5 años de experiencia práctica en procesamiento de señales de radar en defensa o automoción.
✓Experto en procesamiento de señales en sistemas FMCW o pulsados con enfoque en radar de alta resolución.
✓Habilidad demostrada en algoritmos de detección y seguimiento de objetivos móviles (EKF/UKF).
✓Experiencia en implementación en plataformas embebidas con restricciones de tiempo real y recursos.
✓Capacidad para prototipar, probar y validar algoritmos en entornos HIL, cámaras anecoicas y vuelo real.
✓Altos niveles de autonomía, rigurosidad matemática y pensamiento crítico sin dependencia de herramientas automatizadas.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

Inverse SAR (ISAR)Moving Target Detection (MTD)EKF/UKFJamming EstimationSpectral SniffingSpatial Covariance AnalysisEmbedded Computing PlatformsHardware-in-the-Loop (HIL)Anechoic Chamber TestingFlight Validation

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About Us Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces. Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected. About the Role As a confirmed Radar Signal Processing Engineer on Harmattan AI's Radar team in Paris, you will own the signal processing algorithms behind our next-generation airborne radar payload. You will take full ownership of your workstream, from algorithmic research through embedded implementation and flight validation, working with high autonomy and minimal oversight. You will work closely with the EW and RF analytics teams to translate product-level requirements into deployed, mission-ready capabilities. Responsibilities Design and implement near-real-time algorithms for radar image formation, including inverse SAR (ISAR) processing of moving targets. , EKF/UKF-based approaches) for moving target indication on airborne radar data. Build jamming estimation capabilities, combining out-of-band spectral sniffing with in-band spatial covariance analysis, and the adaptive logic that drives radar behavior in response. Contribute radar-derived observables and algorithms that support navigation when GNSS is unavailable. Prototype and port algorithms onto the selected embedded computing platform, balancing algorithmic performance against real-time and resource constraints. Validate algorithms end-to-end through hardware-in-the-loop bench testing, anechoic chamber campaigns, and real flight conditions, iterating quickly on results. Work closely with the EW and RF analytics modules to align signal processing development with system-level requirements. Requirements 2 to 5 years of confirmed, hands-on experience in radar signal processing, gained in the defense or automotive radar industry preferably. Solid experience in Signal Processing on radar systems, either FMCW or pulsed, is required; exposure to moving target tracking, ECCM, radar-based navigation, or live/real-time processing is a strong plus. Strong theoretical foundations and genuine hands-on comfort with the underlying mathematics, not reliance on off-the-shelf tools or LLM-generated solutions. A quick thinker, comfortable taking full ownership of a technical scope end-to-end with minimal oversight. Comfortable working in a fast, iterative cycle: writing code, running hardware-in-the-loop tests, and pushing validated changes independently. We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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