AI Engineer - Simulation EnvironmentsMunich, Limassol

About the role

Your mission The role As an AI Engineer for Simulation Environments, you enter as a key member of the early AI team. You will work directly with our AI leadership and researchers to define the simulated worlds in which our humanoid robots learn and are evaluated. You design training and evaluation environments with state-of-the-art physics engines, build and curate the asset libraries that fill them, and own the large-scale benchmarks that tell us - quickly and reliably - whether a new policy is better. Your environments sit between research, hardware and product, so how well they match reality and how useful they are directly sets how fast and how safely we can bring new capabilities to our robots. This is a full-time, permanent position.Your profile Key responsibilities • Training and Evaluation Environments: Design and build scalable simulation environments for humanoid robots with physics engines such as MjLab and Isaac Lab. Work with AI researchers to create challenging training tasks, curricula and evaluation scenarios. • Asset Management: Build and curate our database of robot, object and scene assets - including import, validation, collision and physics properties, metadata and versioning - so that environments can be assembled quickly and reproducibly. • Simulation Benchmarking: Own rigorous, large-scale simulation benchmarks and evaluation sweeps that enable fast policy evaluation cycles, with statistically sound metrics, regression tracking and clear reporting to research teams. • Sim-to-Real Alignment: Work with hardware and control engineers to align simulation with reality through robot modeling, actuator and sensor models, system identification and validation against real-world data. • Use-Case Driven Environments: Work with product teams to turn real customer use cases into simulated environments and benchmarks that measure what matters for deployment. Who we are looking for We seek people who embrace the empirical nature of AI research and want to accelerate our research velocity with best-in-class tools - so that we can all make breakthroughs faster, together. • Experience: 3+ years of hands-on experience building simulation environments for robot learning with physics engines such as MuJoCo/MjLab, MuJoCo Warp/MJX, Isaac Lab/Isaac Sim or Newton. • Core Skills: Deep understanding of physics simulation and large-scale evaluation infrastructure. In detail: • Simulation Physics: Rigid-body dynamics and contact simulation, including solver parameters, numerical stability and the trade-offs between simulation speed and fidelity. • Assets & Formats: Robot and scene description formats and asset pipelines - URDF, MJCF, OpenUSD, mesh processing and convex decomposition (e.g. CoACD, V-HACD) - and asset validation at scale. • Benchmarking Infrastructure: GPU-parallel simulation, sweep orchestration, reproducibility and statistically sound metrics. • Core Stack: Python, C++, PyTorch and/or JAX, and GPU programming with CUDA or NVIDIA Warp. • A plus: Video game development (e.g. Unreal Engine, Unity or Godot), including level design, procedural content generation and real-time rendering; sim-to-real techniques (system identification, actuator modeling, domain randomization, sensor simulation for cameras, depth, IMU and tactile); photorealistic rendering and scene reconstruction (ray tracing, Gaussian splatting, NeRFs); 3D content tooling such as Blender or Houdini and large-scale asset sources such as Objaverse; familiarity with RL and imitation learning for humanoid locomotion and manipulation • Mindset: You balance the agility of a startup with the professional rigor required for a global industrial player. You are a curious builder who thrives in a collaborative, fast-paced research environment, and a cross-functional collaborator who turns the different needs of research, hardware and product into environments and benchmarks everyone trusts. Why us? • The Team: Work alongside leadership with a proven track record of building unicorn-scale companies and defining global robotics standards. • Smart Strategy: We operate as disciplined fast followers. Capital is timed to the deployment inflection point, avoiding early-mover dead ends to scale fast on proven foundations. • Resources: We are substantially internally funded and attract top-tier investors to avoid any capital constraints for our mission. • Historic Opportunity: Join at the dawn of a new industry comparable to the rise of the automobile. Help shape the European champion in this trillion-dollar market.