Flight Control & Dynamics Engineer

Harmattan AI; Paris; Vor Ort; EUR 85.000 - 125.000; Vollzeit

Zusammenfassung

Harmattan AI is seeking a Flight Control & Dynamics Engineer to own control law design and system identification for high-speed autonomous flight across a family of airframes. The role is based in Paris, with possible work from Lausanne or Zurich.

You will balance classical vs learning-based methods, develop simulation-to-flight pipelines, and mentor junior control engineers as the team grows. Ideal candidates have hands-on flight data modeling, real-time embedded implementation, and experience

Qualifikationen

• Degree in aerospace, controls, robotics, or related STEM field.
• Hands-on identification and control on multirotor or fixed-wing platforms.
• Real-time control on microcontrollers and companion computers.
• Experience with reinforcement learning and simulation-based training.
• Commitment to Harmattan AI’s mission.

Aufgaben

• System Identification design and model fitting from flight data.
• Design and tune control laws for multiple airframes.
• Ensure sim-to-real fidelity in in-house simulator.
• Flight testing and diagnosis across SITL/HITL.
• Mentor junior engineers depending on seniority.

Kenntnisse

System Identification

Control Tuning

Embedded Realization

Reinforcement Learning

Aerospace Engineering

Ausbildung

Bachelor/Master in Aerospace, Controls, Robotics

Jobbeschreibung

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

Harmattan AI is pushing the boundaries of high-speed autonomous flight, where control has to hold up at the edge of the envelope. Getting that right across a family of airframes is one of the most demanding parts of the flight software.

As a Flight Control & Dynamics Engineer, working out of Lausanne, Paris, or Zurich, you will own control law design and the system identification that feeds it, setting the control standard as the team grows. You will weigh classical against learning-based methods, from tuned control laws to reinforcement-learning policies trained in simulation and flown on hardware, and decide what actually flies.

RESPONSIBILITIES

• System Identification: Design excitation maneuvers and fit airframe models from flight data, with quantified error bounds.




• Control Law Design & Tuning: Inner rate and attitude loops through outer position loops, with allocation, gain scheduling, and manual or automated tuning across the airframe family and flight envelope.




• Sim-to-Real: Keep the in-house simulator faithful to the identified model, so control developed in simulation transfers to the aircraft.




• Model Consumption: Turn the stability derivatives and coefficient tables from Aerodynamics into flying control.




• Flight Test & Diagnosis: Verify across simulation, SITL, and HITL, including Monte Carlo campaigns, then fly and iterate from logs.




• Mentorship: Depending on seniority, support the team by mentoring junior control and GNC engineers.

CANDIDATE REQUIREMENTS

• Educational Background: A strong academic record with a degree in aerospace, controls, robotics, or a related STEM field. A practical track record matters more than the specific degree.




• System Identification & Control: Proven, hands-on identification and control on multirotor or fixed-wing platforms, validated in flight, with depth in at least one of MPC, INDI, or geometric control.




• Embedded Realization: Real-time control implementation on constrained targets, split cleanly between a microcontroller and a companion computer.




• Learning-Based Control: Familiarity with reinforcement learning and simulation-based training, and the judgment to know when a learned policy beats a classical design.




• Professional Attributes:




• Bonus: Multi-airframe or hover-to-cruise transition experience.




• Commitment: 100% dedication to Harmattan AI’s mission of providing a defensive edge to allied nations through ethical, high-impact technology.

We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.