Staff, Software Engineer - Simulation Vehicle Modeling

Remote - US,

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 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 maintain key technical systems across multiple repositories and contribute to cross-org architectural decisions.

• Operates as an advanced-level professional with wide latitude for independent judgment and minimal supervision.

• Track record of mentoring engineers and contributing to technical direction within the simulation and autonomy domains.

Bonus Points!

• Experience as technical lead for a vehicle simulation sub-team, driving architecture across vehicle types, sensor platforms, and fleet variability.

• Experience with high-fidelity truck & trailer or heavy-vehicle models.

• Experience building or extending closed-loop autonomous vehicle simulation environments at scale.

• Familiarity with scenario-based validation and sim-to-real correlation activities.

• Familiarity with how learned models (neural networks) consume simulation and vehicle model outputs in autonomy V&V workflows.