About the Role

We're looking for a sharp, hands-on engineer to join a small, high-output team building real autonomous systems. You'll develop high-fidelity platform simulations, design and implement control and navigation algorithms, and take them all the way through to hardware deployment and field testing. This isn't a purely theoretical role — you'll be expected to get your hands dirty in the lab and in the field.

We operate with a high degree of autonomy. You'll be expected to work independently, drive your own tasking, and take ownership of your work in alignment with the team's broader goals.

This is a hybrid role, combining focused independent work with in-person work as required for hardware integration, and field testing.

What You'll Work On

• Developing high-fidelity dynamics simulations for robotic platforms (UGVs, UAVs, AUVs, or similar)

• Implementing and tuning GNC algorithms including path planning, state estimation, and feedback control

• Deploying algorithms to embedded hardware and validating behaviour against simulation

• Writing production-quality, maintainable code under real hardware constraints

• Field testing and iterative tuning on physical platforms

Who We're Looking For

You'll be a good fit if you meet one of the following:

• Student or recent graduate with demonstrated academic excellence in control systems, linear algebra, numerical analysis, or machine learning (Bachelor's degree in Engineering, Mathematics, Computer Science, or related field, in progress or completed)

• Early-career engineer with 1–3 years of industry experience implementing control systems on motion platforms (UGVs, UAVs, AUVs, or equivalent)

• Self-taught or non-traditional candidate who can demonstrate equivalent expertise through projects, open-source contributions, or a technical challenge

Technical Requirements

• Proficiency in at least two of: Python, MATLAB, Julia, Rust, C/C++, or another systems-level language

• Comfortable working with embedded or resource-constrained hardware environments

• Familiarity with agentic programming and prompt engineering: you know how to leverage LLM-assisted workflows and, critically, how to validate and test what they produce

• You have an opinion on Linux vs Windows for robotics workflows (spoiler: we use Linux)

What Will Set You Apart

• Hands-on experience with simulation frameworks (JSBSim, Gazebo, Simulink, Mujoco, Drake, or similar)

• Exposure to sensor fusion, Kalman filtering, or state estimation, PID, Modern Control, path planning

• Experience with version control and collaborative development workflows

• Electronics experience — comfortable reading schematics, working with sensors and actuators, or debugging hardware at the component level

• A GitHub profile, thesis, or side project that shows us what you can build

What to Expect

You'll be given real responsibility from day one and expected to manage your own workload with minimal hand-holding. Flexibility and a pragmatic problem-solving attitude matter as much as technical depth.

Don't Tick Every Box?

If you haven't done everything listed here but believe you can, and the idea of figuring it out doesn't scare you — we want to hear from you anyway. Get in touch.