Junior Mechanical Engineer – Quadcopter Systems

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 guidance turns intent into a flyable path at speed. It takes a mission objective or a waypoint, produces the reference, and drives the aircraft along it. It is one of the most demanding parts of the flight software. As a Flight Guidance & Motion Planning Engineer, working out of Lausanne, Paris, or Zurich, you will own motion planning, trajectory generation, and guidance laws, consuming imperfect, delayed inputs from the estimator and the perception pipeline and handing references to the control loop. You will weigh classical against learning-based methods, from optimization-based planning to learned and differentiable approaches, and decide what holds up at high speed. RESPONSIBILITIES * Motion Planning: Plan dynamically feasible paths onboard, including obstacle avoidance, replanning as the situation changes, and perception-aware planning. * Trajectory Generation: Turn those paths into feasible references under airframe and actuator limits, handed cleanly to the control loop. * Guidance Laws: Design the laws that steer the aircraft along the reference and hold it there. * Interfaces & Perception Coupling: Own the input contracts for the ego-state from Navigation and the perception pipeline, and handle their latency, rate, and dropout, including behavior when an input drops. * Mode & Failsafe Logic: Across cruise, loiter, and approach, including lost-link behavior. * 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 engineers. CANDIDATE REQUIREMENTS * Educational Background: A strong academic record with a degree in aerospace, robotics, GNC, or a related STEM field. A practical track record matters more than the specific degree. * Motion Planning & Trajectory: Proven experience with onboard motion planning, trajectory generation, and tracking, and with guidance laws on flying platforms. * Perception-Coupled Control: Hands-on experience closing a control loop on a perception output, handling latency and dropout. * Learning-Based Methods: Familiarity with learning-based planning or guidance and simulation-based training, with the judgment to weigh it against classical approaches. * Professional Attributes: * Systems-minded and pragmatic about failure modes and imperfect inputs, disciplined about simulation and validation. * Communicates clearly, able to present guidance and test results to engineers and senior stakeholders. * Thrives under pressure in a fast-paced environment with a no-task-is-too-small mentality. * Bonus: Experience with vision-based or perception-coupled guidance. * 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.

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: * Empirical and hardware-honest, disciplined about experiments and validation, grounded in real flight data. * Communicates clearly, able to present control and test results to engineers and senior stakeholders. * Thrives under pressure in a fast-paced environment with a no-task-is-too-small mentality. * 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.