Senior Unreal Engine / Simulation Engineer

Company Description immersiVERSE provides an end-to-end perception development and validation solution for industrial deployment of autonomous systems, built on hyper-realistic environments and multi-sensor fusion. The company’s platform is the result of over five years of refinement before incorporation, giving customers a mature, production-ready solution rather than an early-stage prototype. By covering the full perception lifecycle, from realistic digital environments and synthetic data generation to ML training and structured validation, immersiVERSE helps organizations shorten development cycles and reduce technical risk. Its focus on rare events, failure modes, and adverse conditions enables more robust perception where autonomous systems most often fail, improving reliability before real-world deployment.

Role Description This is a full-time, hybrid Senior Unreal Engine / Simulation Engineer role based in the Greater Barcelona Metropolitan Area, with flexibility for partial work from home. The role involves designing, implementing, and optimizing interactive, hyper-realistic simulation environments in Unreal Engine to support perception development and validation for autonomous systems. Day-to-day responsibilities include building high-fidelity physics-based simulations, integrating multi-sensor data, and collaborating with ML and perception teams to create scenarios that expose edge cases and failure modes. The Senior Engineer will develop tools and workflows to generate synthetic data at scale, profile and tune simulation performance, and ensure technical robustness and reproducibility across diverse conditions. The role also includes reviewing code, mentoring colleagues, and contributing to architectural decisions that keep the simulation platform scalable, maintainable, and aligned with customer needs.

Qualifications

• Strong analytical skills, including quantitative problem-solving and the ability to interpret complex simulation and perception results.
• Hands-on experience with simulation software and simulations, preferably using Unreal Engine or similar real-time 3D engines for physics-based and sensor-driven environments.
• Background in mechanical engineering or a related field, with practical exposure to modeling dynamic systems and hardware–software interaction.
• Proficiency in C++ and Blueprint scripting in Unreal Engine, with solid software engineering practices (version control, testing, code review).
• Experience building or integrating sensor models (e.g., camera, LiDAR, radar) and working with data pipelines for synthetic data generation.
• Comfort working in a hybrid environment, collaborating effectively with cross-functional teams, and communicating clearly in English.
• Bachelor’s or Master’s degree in Computer Engineering, Mechanical Engineering, Physics, or a related technical discipline, or equivalent professional experience.
• Experience in autonomous systems, robotics, or perception/ML workflows is highly beneficial.

Mission Build the high-fidelity simulation and scalable synthetic-data generation infrastructure.

Responsibilities

• Develop high-fidelity environments in Unreal Engine.
• Build and optimize simulation of cameras, LiDAR, depth and other sensors.
• Implement drone/robot viewpoints and sensor synchronization.
• Develop procedural scenario and environment generation.
• Implement domain randomization for lighting, weather, objects and environments.
• Build high-performance off-screen/headless data-generation pipelines.
• Integrate physics, robotics models and ROS 2.
• Optimize GPU/CPU utilization for large-scale parallel simulation.
• Generate precise 2D/3D ground truth directly from simulation.
• Package simulation environments for cloud/server deployment.

Requirements

3+ years Unreal Engine development, preferably C++. Strong C++ and Blueprint knowledge. Experience with Unreal rendering, Scene Capture, Niagara and physics. Understanding of LiDAR/camera/depth sensors. ROS 2 experience. GPU optimization and robotics/autonomous systems experience are strong advantages.

Key Performance Indicator

Key KPI: Millions of high-quality simulation samples generated efficiently and reproducibly.