13 days ago
Responsibilities
- Build and extend the simulation environment, including production autonomy-stack integrations, consumed interfaces, vehicle and actor models, and environmental and operational conditions.
- Maintain simulation integration as the autonomy stack evolves and improve fidelity between simulated and real inputs.
- Build and operate cloud-based scenario execution covering orchestration, parallelism, result aggregation, artifact capture, and runtime cost modeling.
- Develop evaluation layers with precise assertions and pass/fail criteria suitable for release gating.
- Build failure-triage tooling including failure clustering, per-failure recordings, and dashboards.
- Extend scenario-authoring tools used by the verification and validation team across backend and frontend systems.
- Maintain simulation foundations including determinism, reproducibility, pipeline performance, and coverage across maps and sites.
- Own ongoing test quality and reduce flaky failures through reproducibility, determinism, and gate validation.
Requirements
- Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or a related field.
- Strong Python skills and a record of writing 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 a proprietary simulator.
- Working knowledge of simulation, modeling, and validation methodology for relating simulated results to real-world behavior.
- Experience with Docker, Linux, distributed-systems fundamentals, 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 for distributed, GPU-bound systems.
- Preferred: a master’s degree in Computer Science, Robotics, or a related field.
- Preferred: experience with safety-critical autonomous driving, aerospace, or robotics systems; autonomous vehicle software stacks; cloud-based simulation infrastructure; sensor modeling; automated testing; recorded-data re-simulation; and determinism or test-signal quality work.
- Preferred: exposure to ISO 26262, ISO 21448 (SOTIF), UL4600, and ISO 13849.
About AeroVect
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