Staff, ML Engineer - Learned Behaviors / RL Planning
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The role
You will lead the architecture, development, and validation of RL-driven learned behavior models (e.g., driver mimicry, multi-agent interaction, behavior cloning) for highway and freight-truck autonomy.
Define and implement data strategies to collect, label, and curate large behavior datasets from in-vehicle logs, simulation, and fleet data for training and evaluation.
Develop scalable model training pipelines, infrastructure, and tooling to move from prototype to production deployment.
Design and track performance metrics, analyze model behavior, diagnose failure modes, and drive continuous improvement in simulation and on-vehicle operation.
Collaborate with simulation, scenario, and validation teams to embed learned behavior models into verification and validation frameworks, ensuring coverage across operational design domains.
Mentor and lead mid and senior ML engineers, set technical direction, and promote best practices in learned behavior engineering across the team.
Define and implement data strategies to collect, label, and curate large behavior datasets from in-vehicle logs, simulation, and fleet data for training and evaluation.
Develop scalable model training pipelines, infrastructure, and tooling to move from prototype to production deployment.
Design and track performance metrics, analyze model behavior, diagnose failure modes, and drive continuous improvement in simulation and on-vehicle operation.
Collaborate with simulation, scenario, and validation teams to embed learned behavior models into verification and validation frameworks, ensuring coverage across operational design domains.
Mentor and lead mid and senior ML engineers, set technical direction, and promote best practices in learned behavior engineering across the team.
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