Staff, ML Engineer - Learned Behaviors / RL Planning

📋 Description

• • As a Staff Learned Behaviors Machine Learning Engineer at Torc Robotics, you will be at the forefront of developing and deploying advanced Reinforcement Learning (RL)-driven behavior models specifically designed for autonomous trucks. This pivotal role demands a blend of technical leadership, deep machine learning expertise, and a collaborative spirit to drive the next generation of safe, efficient, and human-like decision-making in self-driving vehicles.
• • You will architect, develop, and rigorously validate sophisticated learned behavior models. This includes exploring and implementing techniques such as driver mimicry, multi-agent interaction modeling, behavior cloning, and advanced reinforcement learning algorithms tailored for the complexities of highway driving and freight-truck operations.
• • A critical aspect of this role involves defining and executing robust data strategies. You will be responsible for the collection, meticulous labeling, and curation of vast datasets encompassing in-vehicle data, simulation logs, and real-world fleet data, all essential for training and evaluating your models.
• • You will design, build, and maintain scalable model training pipelines and the underlying infrastructure. This includes developing tooling that enables rapid iteration from initial prototype to production-ready deployment, ensuring efficiency and agility in the development lifecycle.
• • A key responsibility is the design and tracking of performance metrics. You will meticulously analyze model behavior, diagnose failure modes, and leverage these insights to drive continuous improvement of learned behaviors, both in simulation environments and on actual vehicles.
• • Collaboration is paramount. You will work closely with simulation, scenario, and validation teams to seamlessly integrate learned behavior models into comprehensive verification and validation frameworks. This ensures that the models are thoroughly tested and perform reliably across the entire spectrum of Operational Design Domains (ODDs).
• • This is a technical leadership position focused on innovation and elevating the maturity of our ML models. You will mentor and guide mid-level and senior ML engineers, setting the technical direction for the team and championing best practices in learned behavior engineering.
• • Your work will directly impact the safety, efficiency, and overall performance of Torc's autonomous trucking solutions, contributing to the company's mission to revolutionize freight transportation.
• • You will be instrumental in bridging the gap between cutting-edge ML research and practical, real-world application in the challenging domain of autonomous vehicles.
• • The role requires a deep understanding of the entire ML lifecycle, from data acquisition and preprocessing to model training, evaluation, deployment, and ongoing monitoring.
• • You will contribute to the strategic roadmap for learned behaviors, identifying opportunities for advancement and ensuring alignment with the company's long-term vision for autonomous driving technology.
• • This position offers a unique opportunity to shape the future of autonomous trucking by developing intelligent systems that can navigate complex scenarios with human-like adaptability and foresight.
• • You will be expected to stay abreast of the latest research and advancements in machine learning, particularly in areas relevant to autonomous systems and behavioral modeling, and to apply this knowledge to solve real-world problems.
• • The role involves a significant amount of problem-solving, requiring creative approaches to tackle complex challenges in perception, prediction, and planning for autonomous vehicles.
• • You will play a key role in ensuring the robustness and reliability of our autonomous driving software by developing sophisticated learned behavior models that can generalize across a wide range of driving conditions and scenarios.
• • This position is ideal for an experienced ML engineer who thrives in a fast-paced, innovative environment and is passionate about making a tangible impact on the future of transportation.