Staff, ML Engineer - Learned Behaviors / RL Planning

Lead architecture, development, and validation of learned behavior models (e.g., driver mimicry, multi-agent interaction, behavior cloning, reinforcement learning) for highway and freight-truck autonomy. Define data strategies to collect, label, and curate large behavior datasets (in-vehicle, simulation, fleet logs) for training and evaluation. Develop scalable model training pipelines, infrastructure, and tooling to iterate quickly on behavior models, from prototype to production deployment. Design and track performance metrics, analyze model behavior, diagnose failure modes, and drive continuous improvement of learned behaviors in simulation and on-vehicle. Collaborate with simulation, scenario, and validation teams to embed learned behavior models into verification and validation frameworks, ensuring coverage across operational design domains (ODDs). Mentor and lead mid and senior-level ML engineers, set technical direction, and drive best practices in learned behavior engineering across the team.