Staff, Software Engineer - Simulation Vehicle Modeling

About the Company   At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.  Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.  Meet the Team   At Torc, our simulation teams are building the foundation for AV 3.0 driver-out development and certification. This team serves as the critical technical interface between simulation/modeling and autonomy consumers. By ensuring model fidelity, coverage, and usability, the team plays a vital role in evaluating and advancing autonomous driving software. We support massive-scale, parallel execution for scaled verification and validation (V&V) and high-throughput reinforcement learning (RL) training. Ultimately, we provide the framework and tooling that serves Autonomy, Safety, and Release with shared artifacts, common metrics, and deterministic reproducibility.   What You'll Do Own and evolve the technical architecture for scalable vehicle modeling and simulation — extensible across vehicle types, sensor platforms, and fleet variability as Torc's autonomy program grows. Develop and own high-fidelity truck and vehicle dynamics models (longitudinal, lateral, and transient behavior) spanning nominal, off-nominal, and failure-mode simulation domains. Define and drive the statistical validation metrics that directly support Safety Case claims, ensuring model fidelity and coverage meet the bar required for driver-out certification. Design and scale robustness testing frameworks — including controller/planner interaction testing — to stress-test autonomy software at the fidelity and throughput required for large-scale V&V and RL training. Design, develop, and maintain high-fidelity simulation platforms used to validate autonomous driving software in closed-loop evaluation pipelines at scale. Partner with autonomy engineering teams to capture and implement vehicle model requirements supporting planning, controls, and system-level V&V activities. Own model capability communication, known limitations, and release notes to enable effective autonomy validation across consuming teams. Ensure vehicle model updates don't regress autonomy V&V system performance, using automated regression frameworks you help define. Execute full software development lifecycle activities primarily in C++ within a Linux environment and ROS/ROS2 tooling, applying Lean-Agile methodologies. Perform root cause analysis on complex issues surfaced in simulation runs and hardware-in-the-loop testing. Drive test plan design for data acquisition and telemetry supporting field data collection and vehicle model refinement. Set direction for system-level test plans and verification strategies across the simulation org. Communicate technical direction, design decisions, and blockers clearly at stand-ups, design reviews, and cross-org architecture discussions. Build and maintain collaborative relationships with OEM partners and simulation tool vendors to evaluate, integrate, and co-develop simulation capabilities. Mentor engineers across the simulation and autonomy domains and help raise the bar on code quality, process, and testing rigor. What You'll Need to Succeed Bachelor's Degree in Computer Science, Robotics, Mechanical Engineering, Electrical Engineering, or a related technical field plus 10+ years of relevant experience; or Master's Degree in the above fields plus 7+ years; or PhD plus 3+ years. Deep proficiency in C++ (primary), Python for tooling, ROS/ROS2, CMake, and Linux. Strong background in physics-based modeling of ground vehicles, including longitudinal/lateral dynamics, tire models, and powertrain. Working knowledge of AV autonomy stack architecture — planning, controls, and system integration — to collaborate effectively with autonomy engineering teams and ensure vehicle models meet V&V requirements. Demonstrated ability to translate vehicle model capabilities and limitations to autonomy engineering teams, and to capture their requirements to inform model fidelity improvement initiatives. Experience defining statistical validation metrics and robustness testing frameworks used to support formal safety case claims. Experience with unit, integration, and regression testing, automated validation pipelines, and simulation-based performance benchmarking at scale. Track record of driving technical consensus across simulation, autonomy, controls, product, and safety teams — this role is expected to help set direction, not just execute against it. Ability to own and mainta