Why Aidoptation?

At Aidoptation, we work on the hardest problems in autonomous driving: high-speed, safety-critical scenarios where precision and robustness matter. Our technology is proven at racing speeds and translated into real-world highway autonomy. To succeed, we recruit the best engineers globally. We receive a high volume of applications and referrals and select for excellence and commitment alongside deep technical competence.

What You Will Do

In this role, you will lead the development of path and trajectory planning for high-speed highway autonomy, with responsibility for generating safe, feasible, and high-quality motion under real-world system constraints. You will design planning solutions for core highway behaviors such as lane keeping, lane changes, obstacle avoidance, and safety-critical fallback maneuvers, with particular emphasis on robustness to perception uncertainty, localization error, and timing imperfections. You will implement real-time planning algorithms across sampling, optimization, lattice, and MPC-based methods, and ensure they operate effectively within production compute budgets. Working closely with controls and vehicle integration, you will translate planning intent into dynamically feasible trajectories that respect curvature, jerk, and actuation limits while maintaining smooth and predictable behavior on the vehicle.

Requirements

Must-Haves

• PhD with 2+ years of equivalent industry experience or MSc in Robotics, Computer Science, Control, or similar, with 5+ years of equivalent industry experience.

Nice-to-Haves

• Experience with uncertainty-aware planning, probabilistic safety, or formal verification methods.

• Exposure to vehicle dynamics constraints, tire limits, and controller integration.

• Experience with OpenDRIVE/OpenSCENARIO, scenario-based testing, or simulation platforms.

• Familiarity with functional safety concepts (ISO 26262) and SOTIF (ISO 21448).