Machine Learning Engineer II - Learned Planning (Reinforcement Learning) at Torc Robotics

<p><strong>About the Company</strong>&nbsp;</p> <p>At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.&nbsp;</p> <p>A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. <a href="https://torc.ai/daimler-testing-automated-trucks-public/">Now a part of the Daimler family</a>, we are focused solely on developing software for automated trucks to transform how the world moves freight.&nbsp;</p> <p>Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.&nbsp;</p> <p><strong>Meet the Team:</strong>&nbsp;<br>As a Machine Learning Engineer II – Learned Behaviors, you will help develop and&nbsp;deploy&nbsp;&nbsp;behavior&nbsp;models that power decision-making for autonomous trucks. Working closely with teams across&nbsp;perception, prediction, planning, and safety, you will contribute to learned behavior modules that enable safe, efficient, and human-like driving in real-world freight operations.&nbsp;<br>&nbsp;<br>This role focuses on building,&nbsp;validating, and improving machine learning models and infrastructure that support learned behavior systems within the autonomy stack.&nbsp;<br>&nbsp;<br><strong>What&nbsp;You’ll&nbsp;Do</strong>&nbsp;</p> <ul> <li>Develop and train machine learning models for learned behavior systems, including approaches such as behavior cloning, imitation learning, and reinforcement learning.</li> <li>Implement production-quality ML code to support model training, evaluation, and inference within the autonomy stack.</li> <li>Analyze model performance, identify failure modes, and propose improvements to increase robustness and generalization across scenarios.</li> <li>Contribute to model training pipelines and data workflows, curating behavior datasets from simulation, fleet logs, and on-vehicle data.</li> <li>Collaborate with simulation, validation, and autonomy engineering teams to test and evaluate learned behavior models across diverse driving environments.</li> <li>Help integrate learned behavior models into simulation and testing workflows, enabling faster iteration and more comprehensive validation.</li> <li>Support the development of tooling and infrastructure that improves experimentation speed, reproducibility, and model iteration.</li> <li>Contribute to technical discussions around model architecture and training strategies within the team.&nbsp;</li> </ul> <p><strong>What You’ll Need to Succeed</strong>&nbsp;</p> <ul> <li>Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 4+ years of industry experience, or a&nbsp;Master’s&nbsp;degree with 2+ years of experience.&nbsp;</li> <li>Experience applying machine learning techniques such as imitation learning, reinforcement learning, or sequence modeling to robotics, autonomous systems, or complex control environments.</li> <li>Strong programming skills in Python and PyTorch, with experience writing production-quality ML code.</li> <li>Experience training and evaluating machine learning models using large datasets and scalable compute environments.</li> <li>Understanding of ML architectures used in autonomy systems, such as transformers, graph neural networks, or sequence models.</li> <li>Experience debugging model behavior, analyzing performance metrics, and iterating on training pipelines.</li> <li>Ability to collaborate with cross-functional teams to integrate ML models into larger software systems.&nbsp;</li> </ul> <p><strong>Bonus Points!</strong>&nbsp;</p> <ul> <li>Experience working in autonomous driving, robotics, or simulation-based training environments.</li> <li>Experience with reinforcement learning frameworks or distributed training systems (e.g., Ray).</li> <li>Experience working with simulation environments or large-scale behavior datasets.</li> <li>Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems.</li> <li>Experience deploying ML models into production or real-world robotics systems.&nbsp;</li> </ul> <p><strong>Perks of Being a Full-time&nbsp;Torc’r</strong>&nbsp;<br>Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p> <ul> <li>A competitive compensation package that includes a bonus component and stock options</li> <li>100% paid medical, dental, and vision premiums for full-time employees</li> <li>401K plan with a 6% employer match</li> <li>Flexibility in schedule and generous paid vacation (available immediately after start date)</li> <li>AD+D and Life Insurance&nbsp;</li> </ul> <p>At Torc,&nbsp;we’re&nbsp;committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our&nbsp;Torc’rs&nbsp;and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.&nbsp;<br>Even if you&nbsp;don’t&nbsp;meet 100% of the qualifications listed for this opportunity, we encourage you to apply.&nbsp;</p> <p>For this position, we are open to hiring in Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States.</p> <p>Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.&nbsp;&nbsp;&nbsp;<strong> </strong></p> <p><strong>Job ID:&nbsp;</strong> 103006</p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><span style="text-decoration: underline;"><strong>Hiring Range for Job Opening&nbsp;</strong></span></div><div class="title">US Pay Range</div><div class="pay-range"><span>$153,200</span><span class="divider">&mdash;</span><span>$183,800 USD</span></div></div></div>