Simulation Engineer

Title: Simulation Engineer About Us: UnitX builds the world's leading physical AI systems to automate repetitive visual tasks in factories. UnitX is a fast-moving startup with a team from Stanford, MIT, Google, and beyond. Since inception, UnitX has deployed 1,000+ mission-critical systems across 190+ of the world's leading manufacturers' production lines. Every year, $15B worth of products go through UnitX's AI inspection system to ensure quality. Role Overview We are seeking a highly skilled Simulation Engineer to design and build high-fidelity, scalable simulation platforms. In this role, you will architect modular simulation environments that accurately mirror real-world physical interactions and sensor outputs, enabling the robust training, testing, and validation of advanced AI-driven systems. You will play a critical part in closing the sim-to-real gap, ensuring that our simulated environments produce reliable, predictable, and reproducible outcomes in the physical world. Key Responsibilities - Platform Architecture: Design, develop, and maintain a modular, extensible, and customizable simulation platform tailored for scalable AI applications. - Physics & Dynamics Modeling: Leverage state-of-the-art simulation and physics engines to accurately model realistic physical interactions, including rigid body dynamics, complex geometries, and diverse material properties. - Sensor Simulation & Calibration: Develop and calibrate high-fidelity simulation models for diverse sensor modalities. Establish rigorous, quantitative validation metrics to ensure simulated perception accurately matches real-world ground truth. - ML & Synthetic Data Pipelines: Architect scalable pipelines for high-throughput offline synthetic data generation, ensuring seamless integration with machine learning training loops (e.g., Reinforcement Learning, Computer Vision). - Sim-to-Real Optimization: Proactively identify and mitigate risks, failure modes, and bottlenecks for synthetic data generation pipeline. Define and monitor metrics to continually measure and minimize the sim-to-real gap. - Hardware & Environment Modularization: Implement highly configurable asset pipelines to support a wide variety of hardware topologies, sensor configurations, and dynamic operational layouts. - Scaling Future Simulation Diversity: Architect foundational systems capable of supporting next-generation, contact-rich interactions. You will lay the groundwork for our future efforts in advanced domain randomization—expanding spatial, visual, and physical parameters—as our AI models scale in complexity over time. Basic Qualifications - Education & Experience: Bachelor’s degree in Computer Science, Robotics, Engineering, or a related field with 4+ years of professional experience; OR a Master’s degree/Ph.D. with 2+ years of relevant experience. - Industry Track Record: Proven experience contributing to the successful release of a customer-facing product or complex system that heavily relies on simulation (e.g., robotic digital twins, autonomous vehicles, UAV systems, or AAA video games). - Technical Proficiency: Strong software engineering fundamentals with deep expertise in C++ or Python. - Simulation Ecosystems: Hands-on experience with modern simulation frameworks (e.g., NVIDIA Isaac Sim, Drake, MuJoCo) or industry-standard 3D game engines (e.g., Unreal Engine, Unity). Preferred Qualifications - 3D Asset Toolchains: Proficiency with industry-standard 3D asset and robotics description formats (e.g., USD, URDF, MJCF, glTF) and experience building automated CAD-to-sim pipelines. - Machine Learning Integration: Hands-on experience interfacing simulators with modern ML frameworks (e.g., PyTorch, TensorFlow) for synthetic data generation or autonomous agent training. - Advanced Sensor Fidelity: Proven track record of tuning, calibrating, and validating complex simulated sensor suites (e.g., optical, depth, spatial, or tactile sensors) against physical counterparts. - Distributed C