Physical AI Simulation Engineer - Innovation and Data Office - Assistant Director

Job Description

Portfolio:Applied Innovation - Growth & Innovation (ES)

Sub Portfolio:Next Frontier

Role title:Physical AI Simulation Engineer

About the Next Frontier:

Applied Innovation's Next Frontier focuses on emerging technologies, including Physical AI, Quantum Computing, and Next-Generation AI amongst others. This initiative translates advanced capabilities into measurable outcomes, helping clients and EY teams improve decision-making, strengthen resilience, and unlock new opportunities through technology-driven solutions.

About the Delivery Team:

EY advances innovation in Physical AI by enabling regional robotics labs and supporting business-driven initiatives. The focus is on practical Physical AI technologies and framework that deliver measurable, enterprise-value level benefits.

Next Frontier's Physical AI team is led by Youngjun Choi, EY Global Robotics and Physical AI Leader.

Position Summary:

The Simulation Engineer will work on physical AI initiatives. This role requires technical skills NVIDIA Omniverse capabilities to build digital twin simulation.

Essential Responsibilities of the Job:

• Showcase Development: Create Physical AI digital twin simulation, demo contents and video contents
• Develop & Implement: Create interactive 3D environments and digital twins for factories, robots, or infrastructure
• Simulate & Animate: Use PhysX/Isaac Sim for realistic physics, object movement, and event triggers
• Script & Automate: Employ Python for logic, automation, and connecting components

Analytical/Decision Making Responsibilities:

• Assess trends and technologies for relevance and viability in the context of innovative initiatives in the Physical AI workstream
• Prioritize development activities to deliver MVPlevel simulations and digital twin capabilities with a strong sense of ownership and purpose
• Make technical decisions regarding simulation design, physics behavior, animation logic, and automation scripting using platforms like NVIDIA Omniverse, PhysX, Isaac Sim, and Python
• Assess feasibility and technical approach for creating digital twins, interactive 3D environments, and robotic simulations across different infrastructure or factory use cases.
• Identify potential safety, compliance, or scenariocoverage gaps in simulation data and recommend adjustments aligned with Responsible Physical AI governance.

Knowledge and Skills Requirements:

• Familiarity with synthetic data generation techniques (domain randomization, procedural variation, dynamic scene perturbation) to improve robustness of robotics and Physical AI models.
• Knowledge of Responsible Physical AI principles, including data governance, ethics, safety controls, and compliancebydesign, as applied within simulated environments.
• Experience using NVIDIA AI Enterprise or similar accelerated computing platforms to handle largescale 3D simulation datasets and physicsheavy workloads.
• Familiarity with innovation processes and methodologies
• Strong relationship-building, and cross-functional collaboration skills
• Strong sense of purpose and ownership, with an ability to prioritize, deliver MVP products, and encourage those around you.
• Knowledge as well as the ability to strengthen/acquire new knowledge and capabilities to keep up with the continuously evolving technology landscape
• Proven ability to manage high-performing teams and engage stakeholders across various cultures and time zones

Education & Experience:

• Bachelors or Masters in Computer science, Mechanical/Electronics Engineering, Robotics or related fields
• 3-7+ years building simulation environments, digital twins, or robotics testbeds, ideally using Omniverse, Isaac Sim, or equivalent platforms.
• Demonstrated experience developing or consuming synthetic datasets for AI/robotics applications, including scenario creation, annotation, and validation.
• Hands on background with large scale physics simulations, real time rendering systems, or 3D computational pipelines supporting enterprise Physical AI deployments
• Proven track record to ramp up quickly in highly technical domains