AI Simulation Engineer

• Fuse simulation and AI to accelerate training, validation, and edge case discovery for safe autonomous deployment
• Build closed loop systems where on-field data improves simulation, and simulation sharpens real world performance
• Develop simulation driven workflows that generate diverse scenarios, edge cases, and long tail events to improve AI robustness
• Integrate perception, planning, control, and vehicle dynamics models into high fidelity simulation environments
• Create automated validation pipelines that use simulation to stress test autonomy performance across environments, weather, terrain, and failure modes
• Use generative models or data augmentation techniques to expand scenario coverage and reduce reliance on costly on-field testing
• Enhance simulation fidelity by incorporating real world telemetry, sensor data, logs, and environmental conditions
• Develop tools that measure model performance, regression trends, safety margins, and reliability metrics within simulated environments
• Collaborate with autonomy, robotics, data, and test teams to ensure simulation tools and AI workflows reflect real world behavior and operational constraints
• Optimize simulation infrastructure for speed, scalability, and throughput across local, cloud, and distributed compute
• Continuously refine simulation systems, AI training loops, and data feedback pipelines to improve realism and accelerate development cycles

• Experience in AI, robotics, simulation engineering, or machine learning model development
• Strong understanding of simulation environments, synthetic data workflows, scenario generation, or virtual testing systems
• Experience integrating AI models into simulation frameworks for training, validation, or performance testing
• Proficiency in Python, C++, or similar languages used for simulation tools and AI development
• Experience working with robotics concepts such as perception, planning, control, or vehicle dynamics
• Ability to analyze real world data and convert it into simulated scenarios that expose edge cases and system weaknesses
• Experience with cloud simulation infrastructure, distributed compute, or GPU accelerated workloads
• Strong problem solving and analytical abilities, with the skill to bridge real world system behavior and simulated environments
• Ability to collaborate effectively with cross functional engineering teams and communicate technical concepts clearly

Full Benefits - 90% Medical, ESOP, 401K, Generous PTO