Principal Robotics Simulation Architect

The Role: We are seeking a highly skilled Senior Robotics Simulation Expert to join our team. The ideal candidate will be responsible for selecting and advancing simulation architecture solutions tailored for robotic systems. This role requires a deep understanding of robotics simulation stacks, including digital twin development, sim-to-real/real-to-sim pipelines, cloud-based simulation infrastructure, and AI integration within autonomous environments.

Key Responsibilities: Collaborate with cross-functional teams to build and refine robust pipelines for transferring learned behaviors, sensor models, and physics parameters between simulation and real-world robotic systems, minimizing the reality gap through domain randomization and adaptation techniques. Architect and deploy scalable simulation infrastructure on cloud platforms, ensuring seamless parallel simulation runs, distributed training environments, and on-demand access optimized for robotic use cases with low latency and high performance. Provide technical leadership in integrating AI/ML frameworks into simulation environments, enabling reinforcement learning, synthetic data generation, autonomous behavior training, and intelligent environment modeling. Design and implement SIL testing frameworks to validate robotic software stacks—including perception, planning, and control modules—within simulated environments. Develop and maintain HIL testing setups that interface real hardware components with simulated environments, ensuring real-time performance validation, system integrity, and hardware-software compatibility verification. Stay updated with the latest trends and technologies in robotics simulation frameworks, automation, AI/ML integration, and sim-to-real methodologies, offering insights and recommendations to continuously enhance simulation capabilities.

Preferred Experience: Simulation Platforms: Proven experience in simulation architecture using platforms such as NVIDIA Isaac Sim, Gazebo, MuJoCo, Webots, or Unreal Engine, tailored to specific robotic applications. Digital Twin Frameworks: Strong knowledge and hands-on experience developing and maintaining digital twin models for robotic systems, including real-time state synchronization and physics calibration. Sim-to-Real & Real-to-Sim Pipelines: Experience designing domain randomization strategies, sensor noise modeling, and physics engine calibration to bridge the gap between simulation and real-world deployment. Cloud Simulation Infrastructure: Expertise in architecting and deploying simulation environments on cloud platforms including containerized and distributed simulation workflows. AI/ML Integration: Experience integrating machine learning frameworks (PyTorch, TensorFlow, Isaac Lab, or similar) into simulation pipelines for policy training, synthetic data generation, and autonomous behavior development. SIL & HIL Testing: Hands-on experience designing and executing Software-in-the-Loop and Hardware-in-the-Loop testing workflows, including real-time simulation interfacing and embedded system integration. Robotics Frameworks: Proven experience with ROS and ROS2 in simulation and real-world robotic deployments. Problem-Solving Skills: Excellent problem-solving skills and attention to detail in debugging complex hardware-software-simulation interactions. Collaboration and Communication: Ability to work collaboratively in a cross-functional team environment with strong written and verbal communication skills.