AI Simulation Engineer IV
About The Position
At ASI , we are revolutionizing industries with state-of-the-art autonomous robotics solutions. Within the fields of agriculture, construction, landscaping, and logistics, we deliver technologies that enhance safety, productivity, and efficiency. With our core values of Simplicity , Safety , Transparency , Humility , Attention to Detail and Growth guiding everything we do, we're shaping the future of automation in dynamic markets. As an AI Simulation Engineer , you will fuse simulation and AI to accelerate training, validation, and edge case discovery for safe autonomous deployment. This role focuses on building systems where real-world data improves simulation fidelity, and simulation in turn enhances real world model performance, safety, and reliability. You will develop simulation driven training loops, automated validation pipelines, and tools that help autonomy scale faster with higher confidence.
Requirements
- 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.
Responsibilities
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
Number of Employees
51-100 employees
