AV Junior Engineer: Path Planning

AIDOPTATION; Sint-Truiden; Sur place; EUR 40 000 - 70 000; Plein temps

Résumé du poste

A leading firm in autonomous driving is seeking a skilled individual to develop trajectory planning components for highway scenarios. With a focus on real-time algorithms and safety, the role requires expertise in C++ and Python, along with a strong background in motion planning. Ideal candidates will possess a master's degree, relevant experience, and a startup mentality. This full-time position is located in Sint-Truiden, Belgium, with occasional travel for on-vehicle testing.

Qualifications

• 2+ years of relevant industry or research experience.
• Good fundamentals in motion planning and real-time implementation considerations.
• Comfortable with high standards and ownership mindset.

Responsabilités

• Develop trajectory planning components for highway scenarios.
• Implement real-time planning algorithms under compute constraints.
• Collaborate with vehicle dynamics teams to ensure trajectory feasibility.

Connaissances

Motion planning fundamentals

Modern C++ proficiency

Python skills

Linux environment comfort

ROS 2 familiarity

Driving license valid in the EU

Startup mentality

Fluent English

Formation

MSc in Robotics, Computer Science, Control, or similar

Description du poste

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.

Role Description

In this role you will contribute to the development of trajectory planning components for highway scenarios, including maneuvers such as lane keeping, lane changes, and obstacle avoidance. You will work on planners that remain robust under imperfect perception, localization uncertainty, and system latency, while maintaining explicit safety margins.

You will help implement real-time planning algorithms, such as sampling-based, optimization-based, or lattice-style methods, with attention to compute constraints. The role also involves supporting validation through scenario suites, KPIs, and regression testing using simulation and recorded vehicle data.

You will collaborate closely with vehicle dynamics and control teams to ensure generated trajectories are feasible, smooth, and safe at highway speeds. The role includes participation in on-vehicle testing, edge‑case analysis, and rapid iteration to improve system performance. Success in this role means contributing measurable improvements in core scenarios and increasing robustness under real-world conditions. Occasional travel may be required depending on test campaigns.

Requirements

• MSc in Robotics, Computer Science, Control, or similar.
• 2+ years of relevant industry or research experience.
• Good fundamentals in motion planning, constraints, and real-time implementation considerations.
• Proficiency in modern C++ and Python with solid software engineering practices.
• Comfortable in Linux environments and ROS 2 (required).
• Driving license valid in the EU.
• Startup mentality: ownership, speed, and high standards.
• Fluent English (Dutch is a plus).

Nice-to-Haves

• Exposure to uncertainty-aware planning or safety margin design.
• Experience with scenario-based testing or simulation platforms.
• Basic understanding of vehicle dynamics constraints and controller integration.
• Familiarity with OpenDRIVE or OpenSCENARIO formats.

This is a full-time internal position and is not open to external consultants or service providers.