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Helsing is a defence AI company focused on protecting democracies through technological leadership in AI. The company emphasizes ethical development and deployment of powerful technologies.
As a Simulation Engineer, you will be part of a team that owns a system for simulating large-scale 3D worlds containing hundreds of actors, rendered in real time. You will work on the internals of the simulation stack, including modelling of vehicles and other actors, integration of high-fidelity models from domain experts, sensor and environment simulation, networking, and interfacing with other components in a distributed system.
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 Content Engineers into the simulation
- Investigating simulation bugs in order to bridge the gap from simulation to a reference model
- Writing production code that shapes both the simulation platform and the models running inside it
- Translating mission requirements from subject matter experts into reusable simulation models
- Contributing to high-impact projects and collaborating across many teams and backgrounds
REQUIREMENTS:
- 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
- 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
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 (CFD, finite element methods, multi-body dynamics, 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
