Autonomous Flight Guidance & Motion Planning Engineer

Harmattan AI; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Harmattan AI is seeking a Flight Guidance & Motion Planning Engineer, based in Paris (or Lausanne/Zurich), to own motion planning, trajectory generation and guidance laws for high-speed autonomous flight. You will convert objectives into references and drive the control loop within airframe limits.

You will weigh classical vs. learning-based methods, from optimization-based planning to learned approaches, and decide what holds up at high speed.

Qualifications

• Educational background in aerospace, robotics, GNC or related STEM field.
• Motion planning, trajectory generation and guidance laws on flying platforms.
• Hands-on experience with closing a control loop on a perception output.
• Familiarity with learning-based planning or guidance and simulated training.
• Systems-minded, disciplined about simulation and validation, and able to communicate results.
• Bonus: experience with vision-based or perception-coupled guidance.

Responsabilités

• Motion Planning: Plan dynamically feasible paths onboard with obstacle avoidance and replanning.
• Trajectory Generation: Convert paths into references within airframe limits.
• Guidance Laws: Design laws to steer the aircraft along references.
• Interfaces & Perception Coupling: Manage ego-state inputs from Navigation and perception pipeline with latency/dropout handling.
• Mode & Failsafe Logic: Cover cruise, loiter, and approach with safe behavior.
• Flight Test & Diagnosis: Validate in simulation, SITL, and HITL; iterate from logs.
• Mentorship: Mentor junior engineers as needed.

Connaissances

Motion Planning

Trajectory Generation

Guidance Laws

Perception-Coupled Control

Learning-Based Methods

Mentorship

Formation

Degree in aerospace/robotics/GNC or related STEM

Outils

SITL/HITL Testing

Description du poste

Harmattan AI is seeking a Flight Guidance & Motion Planning Engineer, based in Paris (or Lausanne/Zurich), to own motion planning, trajectory generation and guidance laws for high-speed autonomous flight. You will convert objectives into references and drive the control loop within airframe limits.

You will weigh classical vs. learning-based methods, from optimization-based planning to learned approaches, and decide what holds up at high speed.