Autonomous Transport Simulation & Digital Twin Engineer (SNAAP Ribbonway)annical Prototype Assembly Technician

Job Overview:

We are seeking a highly skilled Simulation & Digital Twin Engineer to lead the development of a digital twin for the SNAAP autonomous vehicle and elevated ribbonway system. This role involves creating high-fidelity simulations for traffic flow, safety scenarios, and sensor behavior, as well as modeling the structural design and cost estimates for the ribbonway and station offsets. The ideal candidate will have strong experience with Autoware, ROS2, and advanced simulation environments (e.g., Carla, Gazebo, or SVX - preferred ) and be capable of integrating real-world engineering data into the simulation environment.

Key Responsibilities:

Simulation Development:

• Build and configure high-fidelity simulations of the SNAAP ribbonway, elevated infrastructure, and pod stations using Autoware, SVX(preferred), Carla, Gazebo, or equivalent platforms.
• Model and simulate pod routing, docking, and station "offset" mechanisms (pod pull-ins).
• Create traffic and safety scenario simulations, including collision avoidance, emergency stops, and dynamic flow optimization.

Digital Twin Creation:

• Develop a digital twin of the SNAAP autonomous pod for sensor behavior testing, real-time data collection, and predictive analysis.
• Integrate sensor models (LiDAR, radar, cameras, IMU) into simulations to test perception and planning systems under varying environmental conditions.

Engineering Analysis:

• Collaborate with civil and structural engineers to create cost estimates and conduct materials testing simulations for the elevated ribbonway and station offsets.
• Assist in validating load-bearing capacities, durability, and environmental resilience of materials through simulation-driven testing.

Data and Sensor Integration:

• Implement and analyze simulated sensor data streams to evaluate performance in urban, airport, and other high-traffic environments.
• Provide feedback to hardware and design teams for sensor placement and calibration.

Optimization and R&D:

• Evaluate and optimize pod routing, docking, and operational efficiency based on simulation results.
• Stay current with industry standards for autonomous transport, digital twin technology, and simulation frameworks.

Qualifications:

Education:

• Demonstrated experience and coursework/degree in Robotics, Mechanical Engineering, Computer Science, Civil Engineering, or related field.

Technical Skills:

• Expertise with Autoware (ROS2) for autonomous vehicle simulation and perception/planning stacks.
• Hands-on experience with Carla, Gazebo, SVX, or equivalent simulation environments.
• Strong proficiency in Python, C , or ROS scripting for simulation automation.
• Knowledge of sensor modeling (LiDAR, radar, cameras) and perception algorithms.
• Familiarity with digital twin frameworks and real-time data synchronization.
• Experience in CAD software (e.g., SolidWorks, CATIA) for structural modeling.
• Background in civil or structural engineering principles for cost estimation and materials evaluation is a plus.

Preferred Experience:

• Worked on simulation or digital twins for autonomous vehicles, UAVs, or transportation systems.
• Familiarity with elevated rail or guideway systems and station docking technologies.
• Knowledge of AI/ML-based scenario testing and data analysis pipelines.

Soft Skills:

• Excellent problem-solving and cross-disciplinary collaboration.
• Ability to communicate simulation results and cost analysis to both technical and non-technical stakeholders.
• Self-starter with a passion for innovative transportation systems.

Nice-to-Have Expertise:

• Knowledge of traffic flow theory and microsimulation tools.
• Experience with cloud-based simulation environments.
• Familiarity with embedded systems and real-time ROS integration for hardware-in-the-loop testing.

Why Join Us?

You will be part of a pioneering team redefining urban transportation through the SNAAP autonomous pod system. Your work will directly impact the design, safety, and efficiency of a next-generation elevated transit network designed for smart cities, airports, and urban hubs worldwide.