Senior Software Engineer, Simulation

AeroVect; South San Francisco (CA); Presencial; USD 140.000 - 190.000; Tempo integral

Resumo da vaga

AeroVect in South San Francisco is hiring a role focused on owning and extending the simulation tooling for autonomous ground-handling R&D. The role emphasizes determinism, reproducibility, and test quality to ensure gates can fail reliably and yield actionable information.

You will integrate the simulation with the production autonomy stack, scale scenario execution in the cloud, and build evaluation layers and tooling to support robust, end-to-end validation while reducing flaky failures.

Qualificações

• Bachelor’s or higher in CS/EE/Robotics or related field.
• Hands-on simulation experience for autonomous systems.
• Knowledge of simulation platforms (CARLA, Gazebo, Omniverse) and validation methods.
• Strong Python, Linux, Docker, and distributed-systems know-how.
• Experience with CI/CD and cloud execution for end-to-end validation.

Responsabilidades

• Build and extend the simulation environment integration with the production autonomy stack.
• Maintain determinism and reproducibility, adding fidelity as the autonomy stack evolves.
• Build and operate cloud-based scenario execution with orchestration and result aggregation.
• Develop an evaluation layer to convert runs into precise pass/fail verdicts.
• Create failure-triage tooling, dashboards, and scalable test workflows for V&V.
• Extend scenario authoring tools across backend and frontend, and maintain foundations.

Conhecimentos

Python

Simulation experience

Distributed systems

CI/CD integration

Debugging and profiling

Formação

Bachelor’s in Computer Science, Electrical Engineering, Robotics, or related field

Master’s in Computer Science, Robotics, or related field

Ferramentas

Docker

Linux

CARLA

NVIDIA Omniverse

Gazebo

CI/CD tooling

Descrição da vaga

WHO WE ARE

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com.

You will own and extend the simulation tooling. A significant part of the role is test quality. A test suite that produces flaky failures does not provide usable information. Determinism, reproducibility, and verifying that each gate is capable of failing are ongoing responsibilities rather than one-off tasks.

YOU WILL

• Build and extend the capabilities of the simulation environment: integration with the production autonomy stack, the interfaces it consumes, vehicle and actor models, and the range of environmental and operational conditions that can be represented
• Maintain and improve that integration as the autonomy stack evolves, including fidelity work where the difference between simulated and real inputs changes how the stack behaves
• Build and operate scenario execution in the cloud: orchestration, parallelism, result aggregation, artifact capture, and runtime cost modelling
• Build and extend the evaluation layer that turns a run into a verdict — assertions and pass/fail criteria precise enough to gate a release and stable enough to avoid false failures
• Build failure-triage tooling: failure clustering, per-failure recordings, and dashboards that autonomy engineers can use without assistance
• Extend the scenario authoring tooling used by the V&V team, across backend and frontend
• Maintain simulation foundations: determinism and reproducibility, pipeline performance, and extending coverage to additional maps and sites

YOU HAVE

• Bachelor’s in Computer Science, Electrical Engineering, Robotics, or related field
• Strong Python, with a track record of maintainable code in a shared codebase
• Hands-on simulation experience for autonomous systems, familiarity with simulation platforms such as CARLA, Applied Intuition, Foretellix, NVIDIA Omniverse, IsaacSim, Gazebo, or a proprietary in-house simulator Working knowledge of simulation, modelling, and validation methodology, including how simulated results are used to support claims about real-world behaviour
• Docker and Linux, distributed-systems fundamentals, and experience with GPU-based simulation environments CI/CD and cloud execution, experience integrating automated test workflows into CI for end-to-end validation coverage
• Experience analyzing simulation output and telemetry to identify performance bottlenecks and failure modes
• Debugging and profiling skills suited to distributed, GPU-bound systems

WE PREFER

• Master’s in Computer Science, Robotics, or related field
• Experience designing and validating safety-critical systems in autonomous driving, aerospace, or robotics
• Experience developing or maintaining autonomous vehicle software stacks (ROS/ROS2)
• Cloud-based simulation infrastructure and large-scale distributed test execution
• Sensor modelling (camera, lidar, radar), environment generation, or perception ground-truth pipelines
• Automated testing, continuous integration, and data-driven validation
• Log/bag re-simulation from recorded real-world data
• Test-signal quality work: flake reduction, determinism debugging, golden-output comparison
• Safety standards exposure: ISO 26262, ISO 21448 (SOTIF), UL4600, ISO 13849