About the role
You’ll join a small, highly technical R&D team at Thalanor, working at the intersection of Optimal Control Theory, computer vision and autonomous navigation for UAS.

Your mission is to improve and invent algorithms for guidance and vision, taking state‑of‑the‑art ideas and pushing them further for interception and object detection in complex environments.

On the vision side, you’ll work with deep learning–based object identification, including Long‑Short‑Term Memory vision models where they make sense, to boost accuracy and robustness.

On the autonomy side, you’ll contribute to guidance algorithms grounded in Optimal Control Theory, designing interception strategies and refining trajectories for real drones in the field.

What you’ll be doing

1. Researching and prototyping new algorithms in computer vision and guidance, starting from the latest literature and then adapting, combining or inventing methods that work in practice.
2. Implementing these algorithms in code, iterating quickly from experiments to working modules that can be integrated into our drone systems.
3. Working with concepts such as interception trajectories and statistical filtering (for example, Kalman Filter, Extended KF and Unscented KF) to improve the stability and performance of the overall system.
4. Collaborating closely with other engineers in a startup‑like environment, where autonomy, proactivity and the ability to “figure things out” are essential.

You’ll spend most of your time in hands‑on R&D: reading papers, testing ideas, and turning promising approaches into robust, maintainable code.
If you enjoy moving between theory and implementation and you like seeing your work fly – literally – this role is built for you.

What we’re looking for

1. A strong quantitative background (mathematics, physics, engineering or similar), with genuine enjoyment of mathematical thinking.
2. Solid programming skills, ideally in languages and frameworks commonly used for numerical algorithms and deep learning.
3. Experience in computer vision and/or deep learning for object detection or related tasks; you know how to choose, train and evaluate models, and how to debug them when reality doesn’t match the theory.
4. Familiarity with at least one of the following areas, or the ability to ramp up quickly: Optimal Control Theory, Long‑Short‑Term Memory vision models, Kalman‑family filters.
5. A proactive, startup‑oriented mindset: you like ownership, can manage your own workload, and you’re happy to explore problems that don’t have a predefined solution.

We don’t need you to arrive with deep expertise in every algorithm we use.
What matters is your ability to understand and extend complex methods, plus the drive to build something new rather than simply apply off‑the‑shelf solutions.

Why this will interest you

You’ll be working on technology that sits at the frontier of autonomous flight, in a company where R&D is core to the product rather than an afterthought.

At Thalanor, you’ll contribute to advanced defence systems focused on protection and deterrence, not offensive weapons, and you’ll see your work in live systems, not just in simulations.

Apply using the Apply button, and if you would like to discuss any aspect of the role, contact our Recruiting Manager.