Asks for

The ad says“Familiarity with AI coding tools (e.g. Claude Code, Cursor, Copilot) and agentic orchestration for development.”
The ad says“Several years of relevant experience in robotics simulation, benchmarking, or model-based evaluation, in research or industry.”
The ad says“Strong modern C++ (C++17) and CMake, with Python for tooling; comfortable in large, multi-language codebases.”
The ad says“Familiarity with AI coding tools (e.g. Claude Code, Cursor, Copilot) and agentic orchestration for development.”
The ad says“Strong modern C++ (C++17) and CMake, with Python for tooling; comfortable in large, multi-language codebases.”
The ad says“A working understanding of multi-body dynamics, kinematics, and contact physics — enough to configure, operate, and validate models with confidence.”
The ad says“Familiarity with AI coding tools (e.g. Claude Code, Cursor, Copilot) and agentic orchestration for development.”
The ad says“Familiarity with AI coding tools (e.g. Claude Code, Cursor, Copilot) and agentic orchestration for development.”
The ad says“A working understanding of multi-body dynamics, kinematics, and contact physics — enough to configure, operate, and validate models with confidence.”
The ad says“Several years of relevant experience in robotics simulation, benchmarking, or model-based evaluation, in research or industry.”
The ad says“A working understanding of multi-body dynamics, kinematics, and contact physics — enough to configure, operate, and validate models with confidence.”
The ad says“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.”
The ad says“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.”
The ad says“Strong modern C++ (C++17) and CMake, with Python for tooling; comfortable in large, multi-language codebases.”
The ad says“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.”
The ad says“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.”
The ad says“Several years of relevant experience in robotics simulation, benchmarking, or model-based evaluation, in research or industry.”
The ad says“Experience with — or strong interest in — sim-to-real transfer, and a good understanding of real robot hardware and its limitations.”

Values

The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”

At NEURA Robotics we build cognitive robots and Neuraverse, the connected ecosystem where robots, their skills, and the developers who build them come together. The Cognitive Twin is the unified environment where we design robotic applications, visualize their data in real time, and simulate and run them across virtual and real robots — so an application can be built and validated in simulation long before it runs on real hardware.

The robotics of the future isn't proven on hardware first — it's built and validated in simulation. On the Cognitive Twin team you make the twin's simulation capabilities real and usable: you bring up robots, sensors, and physics scenes on the platform and enable teams to simulate, benchmark, and validate against the real world.

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.