Physical AI Research Engineer

About Remote Robotic Systems

Help build the next generation of autonomous systems operating at the intersection of robotics, aerospace, artificial intelligence, and defence technology.

Remote Robotic Systems (RRS) is a Canadian robotics and defence-tech company helping organizations deploy enterprise-grade drones, uncrewed aircraft, robotic platforms, sensors, payloads, and remote operations technologies for mission-critical applications. Our solutions support customers across defence, public safety, security, industrial, infrastructure, energy, and government sectors.

Through our Airmetal team, we develop advanced aerospace and autonomous systems that support defence, public safety, security, and industrial operations.

As part of this mission, we are building in-house autonomy capabilities that will enable our platforms to operate more intelligently, more reliably, and with greater independence in complex real-world environments.

We're a small, fast-moving team that values ownership, technical depth, practical problem solving, and the ability to translate cutting-edge research into working capabilities.

Airmetal is looking for a Physical AI Research Engineer to help build the next generation of autonomy for our drone platforms.

This is a high-impact role working at the frontier of robotics and physical AI, where you'll evaluate emerging research, develop new approaches, and deploy learning-based autonomy into real-world systems.

You’ll work across the full autonomy development lifecycle, from research and experimentation through training, simulation, testing, and deployment. Working closely with our software lead, you’ll help determine where modern AI approaches outperform classical robotics methods and where hybrid solutions deliver the best results.

We're looking for someone who enjoys exploring new ideas, validating them through experimentation, and translating promising research into practical autonomy capabilities that fly on real hardware.

• Evaluate and reproduce state-of-the-art research in physical AI, robot learning, and autonomous systems.
• Assess open-source frameworks, research papers, and emerging techniques for applicability to Airmetal's autonomy challenges.
• Adapt and extend existing algorithms into solutions tailored to our platforms and operating environments.
• Contribute to the technical direction of autonomy research and development efforts.

• Design, train, and evaluate machine learning models for perception, navigation, control, and autonomous decision-making.
• Develop reinforcement learning, imitation learning, and learning-based autonomy approaches.
• Benchmark AI-based systems against classical robotics and control approaches.
• Help identify where hybrid architectures provide the strongest performance and reliability.

• Develop simulation environments and datasets to support autonomy research.
• Train and evaluate models using in-house compute resources and multi-GPU infrastructure.
• Support sim-to-real transfer through testing, validation, system identification, and domain randomization.
• Work with engineering teams to integrate successful prototypes into production systems.

• Participate in testing and evaluation of autonomy capabilities on real hardware.
• Analyze performance data and continuously improve system behaviour.
• Document experiments, methodologies, results, and technical decisions.
• Help establish best practices for AI research, testing, and deployment across the engineering team.

• Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or a related technical discipline.
• Experience developing machine learning systems for robotics, autonomy, physical AI, or embodied AI applications.
• Experience with reinforcement learning, imitation learning, learned perception, control systems, or related techniques.
• Strong PyTorch experience and practical experience developing, training, and deploying deep learning models.
• Ability to understand, evaluate, and reproduce contemporary research papers and open-source projects.
• Experience with robotics simulation environments such as Isaac Sim, Isaac Lab, Mu Jo Co , or similar platforms.
• Strong Python skills and working proficiency in C++.
• Familiarity with classical robotics concepts including planning, control, estimation, and autonomy.
• Experience working through iterative research and development cycles with a high degree of autonomy.

• Experience with vision-language-action models, world models, diffusion policies, or foundation models for robotics.
• UAV, aerial robotics, PX4, Ardu Pilot, or autonomous drone experience.
• ROS 2 experience.
• Learning-based navigation in GPS-denied environments.
• Visual-inertial estimation, SLAM, or localization experience.
• Multi-agent systems or swarm robotics experience.
• Experience deploying models to embedded systems such as NVIDIA Jetson platforms.
• Contributions to…