Signal Processing Engineer (Radar)

Harmattan AI; Paris (TX); On-site; USD 68,000 - 102,000; Full time

Job summary

Harmattan AI in Paris seeks a Radar Signal Processing Engineer to own algorithms behind airborne radar payloads. You will move from algorithmic research to embedded implementation and flight validation, working with autonomy and cross-functional teams.

Responsibilities include real-time ISAR processing, moving target tracking, and GNSS-denied navigation support. Lead end-to-end development, testing, and iteration on hardware-in-the-loop setups.

Qualifications

• 2 to 5 years of hands-on radar signal processing experience, preferably in defense or automotive radar industries.
• Solid experience in signal processing on radar systems, FMCW or pulsed.
• Strong mathematical foundations and practical coding mastery.

Responsibilities

• Design and implement near-real-time radar image formation algorithms.
• Develop and refine detection and tracking algorithms for moving targets.
• Port algorithms onto embedded computing platforms with attention to real-time constraints.
• Validate end-to-end with hardware-in-the-loop tests and flight-like scenarios.
• Collaborate with EW and RF analytics teams to align processing with system requirements.

Skills

Radar signal processing

Embedded platforms

Algorithm design

Job description

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.




• Develop and refine detection and tracking algorithms (e.g., 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.

Candidate 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.