Senior, Machine Learning Engineer - End-to-End at Torc Robotics

<div> <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.</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> </div> <div><strong>Meet the Team:</strong><br>As a Senior Machine Learning Engineer – End-to-End (E2E), you will develop and scale learning-based systems that connect multi-modal perception inputs to driving behavior, enabling safe, efficient, and human-like autonomy for real-world freight operations.<br><br>You’ll work at the intersection of perception, prediction, and planning, contributing to unified learning pipelines that operate in closed-loop environments. This role focuses on owning meaningful portions of the E2E stack, improving model performance at scale, and driving iteration through data, experimentation, and cross-functional collaboration.<br><br>This is a hands-on engineering role focused on execution, iteration, and delivery.<br><br><strong>What You’ll Do</strong></div> <ul> <li>Own development and delivery of End-to-End ML models that map multi-modal sensor inputs (camera, LiDAR, radar, maps) to driving-relevant outputs (trajectories, cost functions, or intermediate representations)</li> <li>Train and evaluate models using large-scale datasets from fleet logs, simulation, and synthetic data</li> <li>Analyze model performance, identify failure modes, and drive data-driven improvements in robustness and generalization</li> <li>Design and refine training pipelines, data workflows, and evaluation strategies to improve iteration speed and model quality</li> <li>Contribute to model architecture decisions, including approaches such as imitation learning, reinforcement learning, transformers, and vision-language-action (VLA) models</li> <li>Collaborate closely with Perception, Prediction, Planning, and Simulation teams to ensure alignment across the autonomy stack</li> <li>Support integration of E2E models into simulation and on-vehicle systems for closed-loop validation</li> <li>Improve tooling, experimentation workflows, and reproducibility across the team</li> <li>Mentor junior engineers and contribute to team-level best practices and technical discussions</li> </ul> <div><strong>What You’ll Need to Succeed</strong></div> <ul> <li>Bachelor’s degree with 6+ years, Master’s with 4+ years, or PhD with 0–2 years of experience in Machine Learning, Robotics, Computer Science, or a related field with a track record of publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL)</li> <li>Experience developing and deploying ML models for autonomous systems, robotics, or complex decision-making environments</li> <li>Strong programming skills in Python and PyTorch, with ability to write production-quality ML code</li> <li>Experience training and evaluating models using large-scale datasets and distributed compute environments</li> <li>Solid understanding of ML architectures used in E2E systems, such as Transformers, BEV models, VLA/VLM approaches, or diffusion models</li> <li>Proven ability to debug model behavior, analyze performance metrics, and drive iterative improvements</li> <li>Experience contributing to or influencing model architecture and training strategies</li> <li>Ability to work cross-functionally and integrate ML systems into larger autonomy pipelines</li> </ul> <div><strong>Bonus Points</strong></div> <ul> <li>Experience developing End-to-End or mid-to-end models for autonomous driving or robotics</li> <li>Experience with vision-language models (VLMs) or vision-language-action (VLA) systems</li> <li>Familiarity with closed-loop simulation and evaluation frameworks</li> <li>Experience with reinforcement learning or imitation learning in real-world systems</li> <li>Experience with distributed training frameworks (e.g., Ray)</li> <li>Understanding of vehicle dynamics, motion planning, or multi-agent systems</li> </ul> <p><strong>Work Location: </strong>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><strong>Perks of Being a Full-time Torc’r</strong>&nbsp;</p> <p>Torc cares about our team&nbsp;members&nbsp;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;</p> <ul> <li>A competitive compensation package that includes a bonus&nbsp;component&nbsp;and stock options</li> <li>100% paid medical, dental, and vision premiums for full-time employees&nbsp; &nbsp;</li> <li>401K plan with a 6% employer matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures</li> <li>AD+D and Life Insurance&nbsp;&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;</p> <p>Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.&nbsp;</p> <p>Our compensation reflects the cost of labor across several geographic markets.&nbsp;Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience.&nbsp;Torc's total compensation package will also include our corporate bonus and stock option plan.&nbsp;Dependent&nbsp;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;</p> <p><strong>Job ID:&nbsp;</strong>102665</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>$226,400</span><span class="divider">&mdash;</span><span>$271,700 USD</span></div></div></div>