Staff, ML Engineer - Learned Behaviors / RL Planning

10+ years of professional experience in applied machine learning in autonomous vehicles, robotics, simulation or a related domain. M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or related field (or equivalent practical experience). Proven track record of designing and shipping learned behavior or policy models in production or near-production systems. Strong programming skills in Python, Pytorch (Lightning), pandas. Experience with open-source distributed computing framework, specifically Ray. Deep understanding of ML architectures (e.g., RNNs, transformers, graph neural networks, behavior prediction networks) and system-level integration. Experience with large-scale data pipelines, model training infrastructure, versioning, and deployment.

Lead architecture, development, and validation of learned behavior models for highway and freight-truck autonomy. Define and implement data strategies for behavior datasets. Develop scalable model training pipelines, infrastructure, and tooling. Design and track performance metrics, analyze model behavior, and drive continuous improvement. Embed learned behavior models into verification and validation frameworks. Mentor and lead mid and senior-level ML engineers, set technical direction, and drive best practices.