Senior ML/RL Engineer, Behavior Planning

<div class="mt-8 text-xl text-gray-800 leading-8">&nbsp;</div> <div class="mt-8 text-xl text-gray-600 leading-8"> <div data-controller="rich-text"> <div class="rich-text-container" data-rich-text-target="richTextContainer"> <h3><strong>Company Introduction</strong></h3> <p>At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a startup and the wisdom of seasoned experts, our team has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create groundbreaking solutions that propel the future of transportation. Join us and transform your ideas into reality.</p> <h3><strong>Role Overview</strong></h3> <p>We are seeking a <strong>Senior ML/RL Engineer</strong> to join our Algo team and drive the development of our unified behavioral architecture. In this role, you will help bridge the gap between simulation and the real world by developing a scalable policy framework that represents both our L4 ego-policy and a diverse population of simulated agents. You will work at the intersection of Multi-Agent Reinforcement Learning (MARL) and safety-critical system design to ensure our autonomous semi-trucks navigate highways with superhuman safety and precision.</p> <h3><strong>Key Responsibilities</strong></h3> <ul> <li><strong>Behavioral Modeling:</strong> Develop and train diverse, conditioned policies that simulate realistic driving behaviors to stress-test and validate our autonomous driving stack.</li> <li><strong>Safety-Constrained Learning:</strong> Lead the research and implementation of advanced RL algorithms to ensure safety metrics are treated as primary constraints in the learning process.</li> <li><strong>Reward &amp; Objective Design:</strong> Collaborate with cross-functional teams to design robust reward functions and evaluation metrics that balance safety, progress, and comfort.</li> <li><strong>Scalable Training Pipelines:</strong> Contribute to the optimization of our large-scale, high-throughput training environments to enable rapid iteration on complex multi-agent scenarios.</li> <li><strong>Model Architecture:</strong> Advance our state-of-the-art neural architectures to improve spatial reasoning, long-horizon planning, and interaction modeling.</li> <li><strong>Cross-Team Collaboration:</strong> Work closely with Simulation and Planning teams to integrate research-grade models into production-quality, safety-critical software.</li> </ul> <h3><strong>Required Qualifications</strong></h3> <ul> &