About the Job
At the Autonomous Robotics Research Centre (ARRC) of the company, we are seeking a skilled and motivated individual to join our Multi-Robot Coordination team. In this role, you will act as the architectural anchor, ensuring that rapid prototypes and advanced algorithms built by researchers translate into scalable, production-grade systems. You will develop the middleware and the core Sim-to-Real architecture to minimize testing effort across multiple platforms.
If you are passionate about advancing the field of multi-robot coordination and making a significant impact in autonomous robotics in the aerial, ground, and marine domains, we invite you to join our dynamic team at the company. Apply today to be part of our innovative research and contribute to shaping the future of autonomous technologies.
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Responsibilities:
Software Architecture & System Integration
- Design, implement, and maintain robust, scalable software architectures and middleware solutions for multi-agent systems.
- Transition theoretical mathematical models and rapid prototypes into efficient, production-ready code suitable for embedded physical vehicle deployment.
- Write highly efficient, easy-to-read code (C++/Python) and actively participate in peer reviews to enforce software engineering best practices.
Simulation & Sim-to-Real Pipeline
- Build, maintain, and manage high-fidelity simulation environments to validate multi-agent behaviors and coordination logic before physical deployment.
- Own and refine the Sim-to-Real pipeline, minimizing hardware testing risks and ensuring simulated behaviors accurately translate to physical environments.
- Analyze field telemetry and logs to identify Sim-to-Real performance gaps and iteratively improve simulation accuracy.
Field Testing, Deployment & Validation
- Embody the "End-to-End Ownership" model by stepping out of simulation to actively participate in physical, cross-domain field deployments.
- Collaborate closely with researchers and integration engineers to troubleshoot telemetry, network links, and code behavior on physical hardware in real-world conditions.
- Collaborate across other teams to execute joint capabilities like collaborative state estimation and cross-domain coordination.
Required Qualifications and Skills
- Master's degree in Robotics, Control Engineering, Computer Science, or a closely related field.
- Strong programming skills in modern C++ and/or Python, capable of writing functional, production-grade code.
- Deep expertise in building, managing, and navigating high-fidelity robotics simulation environments (e.g., Gazebo, custom physics engines).
- Proven experience bridging the Sim-to-Real gap in robotics, ideally scaling these solutions within Multi-Robot Systems (MRS).
- Extensive experience developing, integrating, and scaling middleware architectures within the ROS2 ecosystem, specifically for multi-agent applications.
- A firm commitment to the "End-to-End Ownership" model: a willingness to take algorithms out of simulation and actively participate in physical field tests.
Nice-to-Have Skills
- Hardware Deployment Experience: Proven hands-on experience deploying robotic systems on physical hardware, ideally executing Multi-Robot Systems (MRS) in field conditions.
- Cross-Domain Autopilot Familiarity: Familiarity with low-level controllers and open-source autopilots across various domains, notably PX4 (which can be leveraged across aerial, ground rovers, and marine platforms), alongside alternatives like ArduPilot, Nav2, or MOOS-IvP.
- CI/CD & Robotics DevOps: Expertise in setting up CI/CD pipelines, containerization (Docker), enforcing coding standards, and managing technical debt in a robotics environment.
- Network & Communications Knowledge: Strong understanding of network latency, intermittent data drops, and cross-domain communication constraints (e.g., WiFi mesh, LoRa, sidelink).
