Simulation Engineer

Typical examples of day-to-day responsibilities include:

• Building and maintaining simulation platform internals: subsystem architecture, replication and multiplayer, performance profiling, and the interfaces used by other systems to orchestrate simulation.
• Composing simulated platforms from sensor, communications, situational awareness, effector, and control-loop models, and reasoning about the underlying physics such as flight dynamics, rigid-body behaviour, collision, and line of sight.
• Owning the trade-off between fidelity, throughput, and engineering cost, choosing the right point for each use case and validating the result against subject matter experts, integration tests, or downstream outcomes.
• Integrating 3D models, animations, and effects from our Content Engineers into the simulation.
• Investigating simulation bugs in order to bridge the gap from our simulation to a reference model.

The day-to-day

You will write production code that shapes both the simulation platform and the models running inside it, and you will decide how each piece of work is validated.

You will also translate mission requirements from subject matter experts into reusable simulation models, and make sure those models remain useful to the teams using simulation as part of their stacks.

You will contribute to high-impact projects and collaborate with people across many teams and backgrounds.

You should apply if you

• Have built real simulations well beyond toy projects, especially with game engines such as Unreal, Unity, or Godot, including gameplay frameworks, replication, and profiling tooling.
• Write production code and bring proper software engineering practice into simulation work, including version control discipline, resolving ambiguity, and designing for the long term rather than the next demo.
• Reason fluently about the trade-off between physical fidelity and simulation throughput.
• Translate input from domain experts into models and behaviours, and know when real-world fidelity is needed and when it is expensive noise.
• Judge a simulation by what it enables rather than by whether it passes its tests, and treat a simulation that quietly misleads its users as a serious failure.

Note: We operate at an intersection where women, as well as other minority groups, are systematically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points.

Nice to have

• Experience with entity-component-system architectures or agent-based modelling.
• Experience with distributed simulation standards such as HLA, DIS, RPR-FOM, NETN, or FMI.
• Background in physics-heavy simulation, for example CFD, finite element methods, multi-body dynamics, or trajectory and 6DoF modelling.
• Experience with RF, electronic warfare, or radar simulation, including propagation and signal processing chains.
• Familiarity with reinforcement learning environment APIs, or with software-in-the-loop and hardware-in-the-loop validation.
• Experience with Rust, CUDA, or MATLAB and Simulink.

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Source: Statistisches Bundesamt (Destatis), table; dl-de/by-2-0; StarIn's calculation