Simulation Engineer – Cognitive Twin (Human)

About NEURA Robotics and the Cognitive Twin Team

At NEURA Robotics, we develop cognitive robots and the Neuraverse ecosystem, connecting robots, their skills, and developers. The Cognitive Twin serves as a comprehensive environment to design robotic applications, visualize data live, and simulate and execute these applications on both virtual and actual robots. This approach enables building and validating applications extensively in simulation prior to deployment on hardware.

We believe future robotics are developed and tested primarily through simulation, rather than exclusively on hardware. As a member of the Cognitive Twin team, you will help bring the simulation capabilities to life, integrating robots, sensors, and physics scenes within the platform. This will empower teams to simulate, evaluate, and validate performances aligned with real-world conditions.

Key Responsibilities

• Deploy and manage the simulation capabilities of the twin atop the platform's physics engine, including configuring rigid-body dynamics, contacts, and articulated components.
• Build and parameterize physics scenes and headless simulation setups, integrating sensors and robots, and facilitating access through web browsers and APIs.
• Create standardized headless benchmark scenes and test cases, monitor them in automated loops, and assess control, planning, and learning methods according to defined fidelity and performance indicators such as update step rate, concurrency, latency, and memory usage.
• Conduct sim-to-real comparisons by analyzing the twin’s behavior against actual robot data logs, identifying noticeable gaps like dynamics inconsistencies or sensor noise, and assisting in simulation parameter calibration to improve fidelity.
• Develop and maintain data pipelines for importing and exporting standard 3D and robot-description formats, ensuring high fidelity round-trip transfers of scene data.
• Own integration of the simulation backend with scene definitions, coordinating representations of composed scenes for runtime engines and managing real-time state streaming in collaboration with integration, frontend, and AI/ML teams.
• Ensure reproducibility and quality by version-controlling scenarios, configurations, and outcomes; establishing modeling conventions and acceptance standards; and producing detailed benchmark documentation.

Qualifications & Experience

• A Bachelor’s or Master’s degree in Robotics, Mechanical or Electrical Engineering, Computer Science, Mechatronics, or a related discipline, or equivalent practical experience.
• Multiple years of relevant experience in robotics simulation, benchmarking, or model-based evaluations in either research or commercial environments.
• Proficiency with modern real-time 3D or game-engine based simulation frameworks and production-grade physics engines such as PhysX, including configuring rigid-body dynamics, articulations, and contact parameters.
• Competency in robot and environment modeling using standard robot-description and scene-interchange formats.
• Sound understanding of multi-body dynamics, kinematics, and contact physics, sufficient for confident simulation configuration and validation.
• Strong skills in modern C++ (C++17 standard) and CMake, complemented by Python programming for tooling purposes, and experience working within complex, multi-language codebases.
• Experience establishing objective evaluation metrics and statistically analyzing simulation results, along with managing structured experiments and automating simulation test workflows including batch runs and continuous integration pipelines.
• Interest or experience in sim-to-real transfer methods and a solid grasp of actual robot hardware constraints.
• Familiarity with AI-based coding assistance tools such as Claude Code, Cursor, or Copilot, and interest in agent-based orchestration supporting software development.
• Preferred skills: knowledge of MuJoCo, NVIDIA Isaac Sim, or PyBullet platforms; GPU-accelerated or distributed simulation; and modeling of actuators and sensors such as IMUs, LiDAR, cameras, and force-torque sensors; proficiency with scene-interchange tooling.
• A focus on product development with the drive to deliver meaningful user value and adapt to evolving product requirements.
• Methodical and organized work habits, collaborative mindset, excellent technical communication skills, fluency in English (German language skills are an advantage).