Software Engineer - Modeling & Simulation

About the role

We are seeking a Modeling and Simulation Engineer to develop and validate software tools for analyzing sensor and vehicle configurations in autonomous systems. This role involves creating accurate models of sensors and vehicles to evaluate technical capabilities and ensure simulations are representative of real-world hardware.

Responsibilities

• Sensor and Vehicle Modeling: Develop accurate models of sensors (e.g., LiDAR, cameras, IMUs) and vehicles to simulate performance under various configurations.
• Simulation Validation: Ensure simulated sensors and platforms closely match physical hardware performance in real-world conditions.
• Software Tooling: Build and maintain software tools for visualizing, analyzing, and optimizing sensor and vehicle configurations.
• Performance Analysis: Conduct technical evaluations of sensor configurations to assess range, accuracy, and other performance metrics.
• Optimization: Explore trade-offs in sensor placement, platform design, and environmental factors to maximize system performance.
• Cross-Functional Collaboration: Work closely with perception, autonomy, and hardware teams to ensure simulation results inform real-world designs.
• Data Visualization: Develop intuitive visualization tools to present complex simulation results to technical and non-technical stakeholders.
• Iterative Improvement: Continuously refine models and tools based on feedback from physical testing and deployed systems.

Requirements

• Education: Bachelor’s, Master’s, or Ph.D. in Robotics, Computer Science, Electrical Engineering, or a related field.
• Sensor Modeling Experience: Proven experience modeling sensors like LiDAR, cameras, IMUs, and GPS in simulation.
• Simulation Tools: Proficiency with simulation frameworks such as Unreal Engine.
• Software Development: Strong programming skills in C++ and Python for building simulation tools and analysis pipelines.
• Data Visualization: Experience creating tools or dashboards for visualizing simulation results.
• Physics-Based Modeling: Familiarity with physics-based simulation techniques for accurate environmental and sensor modeling.
• Systems Integration: Ability to validate and align simulation models with real-world hardware and systems.
• Analytical Skills: Strong ability to analyze and interpret simulation data for performance evaluation.

Preferred Qualifications

• Real-World Hardware Experience: Hands-on experience with physical sensors and understanding of their operational characteristics.
• Optimization Techniques: Knowledge of optimization algorithms for sensor placement or system design.
• Machine Learning: Familiarity with AI/ML techniques for improving simulation fidelity or analyzing sensor data.
• Advanced Visualization: Experience with tools like Matplotlib, Plotly, or 3D visualization libraries.
• Embedded Systems: Understanding of hardware constraints and system-level trade-offs in sensor integration.
• Security Clearance: Active U.S. Secret clearance is a plus.