About the Role
We are seeking a Senior Robotics Engineer to lead motion-planning algorithm development and software engineering for autonomous robotic vehicles at the Autonomous Robotics Research Centre (ARRC). In this role, you will collaborate closely with the motion-planning (MPLAN) Team Lead to translate client requirements into tested planning solutions, maintain and enhance the reusable MPLAN library, and contribute to cutting-edge research and innovation in autonomous robotics.
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Key Responsibilities
- Lead model-based behavior, path, and trajectory planning utilizing search, sampling, and constrained optimization methods.
- Address vehicle constraints, static and moving obstacles, and application-specific terrain requirements through repeated replanning.
- Define project scope, interfaces, acceptance criteria, and technical milestones in collaboration with client teams; effectively communicate risks and limitations.
- Integrate planners with perception, localization, control, and simulation systems; support joint simulator and vehicle testing.
- Oversee the architecture, development, and maintenance of modular planning software, ensuring documented interfaces and the creation of reusable C++ and Python components.
- Establish and supervise code reviews, automated testing, CI/CD, dependency management, and versioned releases to ensure reliable client delivery.
- Mentor engineers and students; collaborate with researchers on learning-based and hybrid planning methods.
- Contribute to research and innovation efforts by preparing manuscripts for submission to leading conferences and journals in control, robotics, and autonomous systems.
Required Qualifications and Skills
- Master's degree or Ph.D. in Robotics, Control, Engineering, Computer Science, Applied Mathematics, or a related field.
- Significant hands-on experience in motion-planning, with a proven track record of technical ownership in software integration and delivery.
- Strong expertise in path planning, trajectory optimization, numerical methods, and constrained optimization techniques.
- Thorough understanding of vehicle kinematics and dynamics, optimal control, and planning-control interfaces.
- Proficient in C++ with practical experience in Python; familiar with ROS/ROS2 and robotic simulation environments.
- Experience with evaluating planners in closed-loop setups and diagnosing integrated system failures.
- Proven ability to translate client needs into actionable requirements, mentor engineering staff, and communicate technical results clearly in English.
- Demonstrated experience in leading robotics software development, including architecture, Git-based collaboration, automated testing, CI/CD, release management, and maintainability.
Desirable Experience
- Familiarity with graph-based and sampling-based path planning methods (e.g., A*, D*, RRT*).
- Knowledge of optimization tools and frameworks like OSQP, acados, and CasADi, or similar.
- Experience with off-road or terrain-aware planning and uncertainty-aware methods.
- Practical experience developing, integrating, or testing motion planning or control algorithms on real autonomous vehicle platforms (ground, marine, or UAV), with an insightful understanding of vehicle dynamics and their implications for planning and control.
- Background in containerized development and deployment (Docker).
- Experience with learning-based or hybrid motion planning approaches is a plus.
Why Join Us?
Joining our team allows you to contribute to groundbreaking advancements that help society tackle significant challenges. We offer a rigorous environment for scientific discovery supported by state-of-the-art facilities and collaborations with leading international institutions. This role will provide you with an opportunity to be at the forefront of innovations in advanced materials, autonomous robotics, cryptography, digital security, directed energy, quantum computing, and secure systems.
