Simulation Engineer – Cognitive Twin (human)

Your mission & challenges

Simulation enablement: You stand up and operate the twin's simulation capabilities on top of the platform's physics engine — configuring rigid-body dynamics, contacts, and articulations, and bringing up robot, sensor, and environment models so scenes run reliably and repeatably.

Scene & content bring-up: You build and parameterize physics scenes and headless setups, wire in sensors and robots, and make simulation features accessible from the browser and the API.

Benchmarking & evaluation: You build standardized headless benchmark scenes and test cases, run them in the loop, and evaluate control, planning, and learning approaches against clearly defined fidelity and performance metrics — step rate, parallel instance count, latency, memory.

Sim-to-real checks: You help compare twin behavior against real-robot logs, surface obvious sim-to-real gaps (e.g. dynamics, sensor noise, contact behavior), and support calibration of simulation parameters as the fidelity bar takes shape.

Interoperability: You build and maintain ingest and export pipelines for common 3D and robot-description formats and own their round-trip fidelity, so scenes move cleanly in and out of the twin.

Platform integration: You own the simulation-backend side of the scene definition format — how a composed scene maps to the engine's runtime representation and how state is emitted over the binary real-time stream — together with Integration, Frontend, and AI/ML.

Reproducibility & quality: You keep scenarios, configurations, and results cleanly versioned and documented, set modeling conventions and acceptance criteria, and produce structured benchmark reports.

What we can look forward to

• A university degree (Bachelor's or Master's) in Robotics, Mechanical / Electrical Engineering, Computer Science, Mechatronics, or a related field — or equivalent hands-on experience.
• Several years of relevant experience in robotics simulation, benchmarking, or model-based evaluation, in research or industry.
• Hands-on expertise with a modern real-time 3D / game-engine-based simulation environment and a production physics engine (e.g. PhysX) — configuring rigid-body dynamics, articulations, and contacts — and confident robot / environment modeling with standard robot-description and scene-interchange formats.
• A working understanding of multi-body dynamics, kinematics, and contact physics — enough to configure, operate, and validate models with confidence.
• Strong modern C++ (C++17) and CMake, with Python for tooling; comfortable in large, multi-language codebases.
• Experience defining objective metrics and statistically evaluating simulation results, plus structured experiment management and automation of simulation tests (batch runs, sweeps, CI-like workflows).
• Experience with — or strong interest in — sim-to-real transfer, and a good understanding of real robot hardware and its limitations.
• Familiarity with AI coding tools (e.g. Claude Code, Cursor, Copilot) and agentic orchestration for development.
• A plus: MuJoCo, NVIDIA Isaac Sim, or PyBullet; GPU-accelerated / distributed simulation; actuator and sensor modeling (IMUs, LiDAR, cameras, force-torque); scene-interchange format tooling.
• A product-development mindset — you care about delivering real value to users and adapt readily as product requirements evolve.
• A structured working style, team spirit, and precise technical communication. Perfect command of English; German is a plus.