Robotics Systems Engineer — 🔒 Filled · Accepting expressions of interest

The role

We're seeking Robot Software Systems Engineers who thrive at the intersection of robotics systems and software architecture. If you're at home in ROS, enjoy wrangling complex software stacks, and can bridge the gap between research-grade algorithms and production robotics—let's connect!

You should be comfortable with ROS ecosystems, familiar with classical robotics packages (planning, perception, control), and have solid backend development skills. The core of this role involves integrating new algorithms and capabilities into our robotics software stack, ensuring everything works reliably together, and building the systems that support our robot learning pipelines.

Your work will span building integration layers between learning algorithms and robot hardware, developing monitoring and control infrastructure, creating simulation and testing frameworks, designing backend services for our robotics workflows, and help shape our overall technical architecture.

About Imitation Machines

Imitation Machines has an ambitious goal of bringing the latest advances in Imitation and Reinforcement Learning, Robotics and AI into an integrated platform that enables anyone in the world to create robot new and custom behaviours.

Imagine the state of future technology where anyone can teach any robot, by demonstration, to solve any task they need, and create intelligent robotic workforce that meets unique needs across industries, robot forms, and environments. We want this future to happen. We see that all the necessary technological prerequisites are in place, and we're building that future. The readiness of reinforcement learning, imitation learning, and robot hardware has reached a tipping point, positioning Imitation Machines to transform how robot behaviours are created. Rather than relying on conventional programming, we can radically accelerate the process and start building systems where robots are taught by human teachers through demonstration.

We're taking a practice-first approach: real-world robot deployments with our industry partners guide our research and development. By working directly with industries, robot developers, and system integrators, we position ourselves at the frontier of practical imitation learning—tackling the challenges that emerge when these technologies meet real applications. This makes us early integrators of imitation learning in production environments, and it's how we're paving the way for broader adoption of robotic automation.

Imitation Machines is a pre-seed funded startup moving quickly toward our next milestone. We're laser-focused on proving our vision and building a team of machines learning and robotics engineers who want to push the boundaries of what's possible in robot learning.

What we’re looking for

• Knowledge of robotics software / control algorithms

• Experience with ROS/ROS2

• Strong intuition of what good code and good software architecture should look like

• Experience with robotics simulators (MuJoCo, Isaac Sim, Gazebo)

• Efficient code development and deployment practices

• Self-driven builder mentality – experimenting, making things happen, thriving on challenges, and breaking new ground

Position details

Level: Entry to mid-level
Type: Full-time
Location: Theoretical, algorithms, and in-simulation work can be done remotely and we do consider fully remote candidates. While based in Sydney is preferred for hardware testing and integration, we welcome strong interstate candidates.
Compensation: As an early-stage startup, we can't always match big tech salaries. What we can offer is the opportunity to work on genuinely hard problems in robot learning, significant autonomy in shaping our technical approach, and the chance to build something from the ground up.
Primary location: Sydney, Australia