Principal AI Engineer - Simulation

Key Responsibilities

Develop Simulation Scenarios:Design, build, and implement simple simulation scenarios and be able to integrate complex scenarios with other teams support in Unreal Engine. This includes creating 3D models, setting up physics and AI behaviors using Blueprints and C++.

Integrate AI Models:Incorporate generative AI and machine learning models into the simulation. For example, integrate large language models or vision-language models to imbue agents and environment elements with intelligent, dynamic behaviors. Ensure smooth integration of external AI for tasks such as decision-making, natural language interaction, or computer vision within the simulated world.

Simulation Experimentation:Conduct simulation-based experiments to test and evaluate AI algorithms and system performance. Set up experiments where autonomous agents or robots interact within the virtual environment and adjust parameters to study outcomes. Analyze results to provide insights on AI behavior and system robustness in a variety of conditions.

Collaboration & Reporting:Work closely with cross-functional teams including AI researchers, software engineers, and domain experts to integrate their requirements into the simulation. Collaborate in an agile manner, iterating on simulation features based on team feedback. Document simulation designs, experiment setups, and results. Clearly communicate progress and findings to stakeholders and contribute ideas to drive innovation within the project.

Required Skills

• Education and Work Experiencemaster's degree in computer science, Engineering, AI, or a related field. Minimum 2 year of working experience in simulation or AI related projects.
• Unreal Engine Proficiency:Hands-on experience with Unreal Engine. Comfortable with both Blueprint visual scripting and C++ for Unreal able to rapidly prototype with Blueprints as well as implement performance-critical systems in C++. Solid understanding of Unreal's physics, AI, and rendering systems to build realistic simulations.
• AI Knowledge:Foundational knowledge of machine learning and AI techniques. Comfortable working with ML frameworks such as PyTorch to integrate pre-trained models or AI components into the simulation. Awareness of generative AI concepts (e.g. large language models, vision-language models) and how they can be applied within simulated environments.
• Problem-Solving & Coding:Strong programming skills in C++ and Python. Able to write clean, efficient, and well-documented code for simulation logic and tooling. Experience with source control and collaborative development workflows. Proven problem-solving ability can troubleshoot simulation issues, debug complex behaviors, and devise creative solutions to achieve desired experimental outcomes.
• Teamwork & Communication:Excellent collaboration skills with an ability to work in multidisciplinary teams. Comfortable communicating with specialists in AI, robotics, or domain experts to gather requirements and explain simulation results. Professional proficiency in English (written and verbal) for documentation and presentations. A proactive mindset with eagerness to learn and share knowledge in a fast-evolving research environment.

Preferred (Bonus) Skills

Digital Twins & Agent-Based SimulationExperience in developing digital twins virtual replicas of physical systems with live data feeds or working on agent-based simulation models. Understanding how to mirror real-world processes in a virtual environment or simulate multiple autonomous agents (e.g., for traffic, crowd simulation, or smart cities) will be valued.

Generative AI ApplicationsPrior experience applying generative AI within simulations (such as using AI to generate scenario content, behaviors or synthetic data) is a plus. This could include projects where NLP models controlled virtual characters, or using GANs/vision models to enhance the realism of the environment.

VR/AR and SensorsFamiliarity with immersive technologies (VR/AR) or sensor simulation is nice to have. For example, knowledge of how to integrate VR for human-in-the-loop simulations, or how to simulate cameras, LiDARs, or other sensors within Unreal Engine, would broaden the impact of your simulation work.

Why Join Us

We are an enthusiastic and innovative team, and joining us means you'll growtremendously as an Simulation engineer. Here are some reasons this role is great for your development:

Mentorship & GrowthLearn from experienced engineers and domain experts who will support your development and guide your learning journey.

Cutting-Edge ProjectsContribute to simulation systems that apply the latest AI models in real-world contexts, expanding your technical skills and innovation potential.

Supportive Team CultureWork in a friendly, collaborative, and inclusive environment. We embrace continuous learning, curiosity, and shared success.