3 months ago
Responsibilities
- Build and extend simulation environments, including production autonomy-stack integration, interfaces, vehicle and actor models, and environmental and operational conditions.
- Maintain simulation fidelity and integration as the autonomy stack evolves.
- Build and operate cloud-based scenario execution with orchestration, parallelism, result aggregation, artifact capture, and runtime cost modeling.
- Develop evaluation layers with precise assertions and stable pass/fail criteria for release gating.
- Build failure-triage tooling including failure clustering, per-failure recordings, and dashboards.
- Extend scenario-authoring tools used by the V&V team across backend and frontend systems.
- Maintain determinism, reproducibility, pipeline performance, and coverage across additional maps and sites.
- Analyze simulation output and telemetry to identify bottlenecks and failure modes, and debug distributed GPU-bound systems.
Requirements
- Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or a related field.
- Strong Python skills and a track record of maintainable code in a shared codebase.
- Hands-on simulation experience for autonomous systems and familiarity with platforms such as CARLA, Applied Intuition, Foretellix, NVIDIA Omniverse, IsaacSim, Gazebo, or proprietary simulators.
- Working knowledge of simulation, modeling, and validation methodology, including using simulated results to support claims about real-world behavior.
- Experience with Docker, Linux, distributed-systems fundamentals, GPU-based simulation environments, CI-integrated automated testing, and cloud execution.
- Experience analyzing simulation output and telemetry to identify performance bottlenecks and failure modes.
- Debugging and profiling skills for distributed, GPU-bound systems.
- Preferred qualifications include a master’s degree, safety-critical systems experience, autonomous-vehicle software-stack experience with ROS/ROS2, cloud-based simulation infrastructure, sensor modeling, environment generation, perception ground-truth pipelines, large-scale distributed test execution, automated testing, real-world data re-simulation, test-signal quality work, and exposure to ISO 26262, ISO 21448 (SOTIF), UL4600, or ISO 13849.
About AeroVect
AeroVect builds autonomous driving systems and software to automate airport ground service equipment, improving ramp logistics for airlines, airports, and ground handling providers. It deploys and supports autonomy for fleets used by major carriers and ground service companies. Founded in 2020 and headquartered in South San Francisco, it is a privately held Series A company.