Autonomy Simulation & Digital Twin Engineer

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Textron Specialized Vehicles Inc. is a leading global manufacturer of golf cars, utility and personal transportation vehicles, professional turf-care equipment, and ground support equipment. Textron Specialized Vehicles markets products under several different brands. Its vehicles are found in environments ranging from golf courses to factories, airports to planned communities, and theme parks to hunting preserves.

Responsibilities:

• Own simulation software configuration management, source control, build automation, and release processes to ensure traceable, repeatable, and validated digital twin environments throughout the product development lifecycle.
• Build a high-fidelity digital twin (physics, drivetrain, sensors) of the vehicle and environment.
• Develop and maintain validated vehicle dynamics models representing steering, braking, drivetrain, and vehicle responses.
• Develop scalable scenario generation frameworks for autonomy verification and validation.
• Generate synthetic training and validation datasets supporting perception development.
• Guarantee simulation scenarios cover all key autonomy modes and edge cases within defined ODD.
• Define simulation coverage metrics to quantify validation completeness and corner-case exposure.
• Develop ground-truth and sensor-fidelity models for camera, LiDAR, radar, GNSS, and inertial sensors.
• Support virtual validation initiatives to reduce physical testing requirements.
• Integrate ROS2 autonomy stack for closed-loop simulation.

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Textron Specialized Vehicles Inc. is a leading global manufacturer of golf cars, utility and personal transportation vehicles, professional turf-care equipment, and ground support equipment. Textron Specialized Vehicles markets products under several different brands. Its vehicles are found in environments ranging from golf courses to factories, airports to planned communities, and theme parks to hunting preserves.

Responsibilities:

• Own simulation software configuration management, source control, build automation, and release processes to ensure traceable, repeatable, and validated digital twin environments throughout the product development lifecycle.
• Build a high-fidelity digital twin (physics, drivetrain, sensors) of the vehicle and environment.
• Develop and maintain validated vehicle dynamics models representing steering, braking, drivetrain, and vehicle responses.
• Develop scalable scenario generation frameworks for autonomy verification and validation.
• Generate synthetic training and validation datasets supporting perception development.
• Guarantee simulation scenarios cover all key autonomy modes and edge cases within defined ODD.
• Define simulation coverage metrics to quantify validation completeness and corner-case exposure.
• Develop ground-truth and sensor-fidelity models for camera, LiDAR, radar, GNSS, and inertial sensors.
• Support virtual validation initiatives to reduce physical testing requirements.
• Integrate ROS2 autonomy stack for closed-loop simulation.

• Education: Bachelor’s degree in Software, Electrical, or Mechatronic Engineer or other related field required.
• Years of Experience: 2+ years of relevant experience required.

• Software Knowledge: Python, C++ or similar programming languages required; ROS2 architecture, Linux development environments, version control systems (Git) required.

Additional Requirements:

• Required Skills: Digital twin development workflows. Experience with simulation platforms and Python-based simulation environments. Understand physics simulation, vehicle dynamics, and sensor modelling. Sim-to-real validation approaches. Experience integrating robotics systems into simulation. Ability to design test scenarios and evaluate simulation outputs. Experience using Git, Azure DevOps or equivalent source-control systems. Familiarity with automated build systems, CI/CD pipelines, and test automation.
• Preferred Skills: Experience with autonomy simulation platforms such as CARLA, Gazebo, Isaac Sim, or Omniverse. Strong understanding of ROS2 architecture. Domain randomization in synthetic data generation for AI/ML. LiDAR, camera, GPS simulation models. Experience with SIL/HIL validation methodologies.

Travel Requirements:

• ~10% travel required to collect ground-truth data, validate simulation fidelity against field results, and support correlation between virtual and real-world testing.
• Valid driver’s license required.

Open to considering remote work for this opportunity. Employees who are working in remote roles will work primarily offsite (from home).

• Education: Bachelor’s degree in Software, Electrical, or Mechatronic Engineer or other related field required.
• Years of Experience: 2+ years of relevant experience required.

• Software Knowledge: Python, C++ or similar programming languages required; ROS2 architecture, Linux development environments, version control systems (Git) required.

Additional Requirements:

• Required Skills: Digital twin development workflows. Experience with simulation platforms and Python-based simulation environments. Understand physics simulation, vehicle dynamics, and sensor modelling. Sim-to-real validation approaches. Experience integrating robotics systems into simulation. Ability to design test scenarios and evaluate simulation outputs. Experience using Git, Azure DevOps or equivalent source-control systems. Familiarity with automated build systems, CI/CD pipelines, and test automation.
• Preferred Skills: Experience with autonomy simulation platforms such as CARLA, Gazebo, Isaac Sim, or Omniverse. Strong understanding of ROS2 architecture. Domain randomization in synthetic data generation for AI/ML. LiDAR, camera, GPS simulation models. Experience with SIL/HIL validation methodologies.

Travel Requirements:

• ~10% travel required to collect ground-truth data, validate simulation fidelity against field results, and support correlation between virtual and real-world testing.
• Valid driver’s license required.

Open to considering remote work for this opportunity. Employees who are working in remote roles will work primarily offsite (from home).