<p><strong>About the Company</strong> </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. </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. </p> <p><strong>Meet the Team</strong><br>As a Staff Machine Learning Engineer specializing in BEV (Bird's-Eye View) and Multi-Modal Perception, you will lead the development of next-generation models that unify information across cameras, LiDAR and radar to deliver a rich spatial understanding of the driving environment. You will drive architectural innovation, large-scale model training, and data-driven improvements that directly advance the perception capabilities at the heart of Torc's autonomous driving stack. This is a technical leadership role focused on model innovation and maturity, not downstream feature integration.</p> <p><strong>What You'll Do</strong></p> <ul> <li>Lead BEV model development: define and execute the technical roadmap for BEV-based perception models across multiple tasks (e.g., detection, segmentation, road topology, and scene understanding).</li> <li>Design advanced multi-modal architectures that fuse heterogeneous sensor data (camera, LiDAR, radar, HD maps) into unified spatial representations.</li> <li>Develop foundational perception models leveraging BEV transformers, voxel-based encoders, or implicit scene representations.</li> <li>Own large-scale training workflows — from data sampling strategies and augmentation pipelines to distributed training and hyperparameter optimization.</li> <li>Advance model robustness and generalization, addressing long-tail conditions such as low visibility, occlusions, and rare scene configurations.</li> <li>Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer performance.</li> <li>Collaborate cross-functionally with sensor calibration, mapping, and fusion teams to ensure cohesive perception model interfaces.</li> <li>Mentor and guide ML engineers, cultivating best practices in experimentation, code quality, and model validation.</li> <li>Stay at the forefront of ML research, exploring self-supervised learning, large-scale pretraining, or foundation models for 3D perception.</li> </ul> <p><strong>What You'll Need to Succeed</strong></p> <ul> <li>10+ years of experience in deep learning for perception, 3D vision, and/or autonomous systems.</li> <li>M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or related field (or equivalent practical experience).</li> <li>Proven expertise in BEV modeling, 3D scene understanding, and multi-view fusion.</li> <li>Strong background in multi-modal sensor fusion, particularly integrating camera and LiDAR data.</li> <li>Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.</li> <li>Experience with large-scale data pipelines, distributed training, and experiment management systems.</li> <li>Demonstrated leadership in driving ML model innovation and mentoring technical teams.</li> </ul> <p><strong>Bonus Points</strong></p> <ul> <li>Experience with autonomous driving or robotics perception in production environments.</li> <li>Experience with MLOps and infrastructure tools (Ray).</li> <li>Hands-on expertise in BEV-based ML architectures, LiDAR-vision fusion, or spatial-temporal modeling.</li> <li>Familiarity with 3D labeling, calibration, and sensor simulation pipelines.</li> <li>Track record of publications or open-source contributions in top-tier venues (CVPR, ICCV, NeurIPS, ICRA, CoRL).</li> <li>Understanding of performance tradeoffs and deployment constraints (latency, memory, accuracy).</li> </ul> <p><strong>Work Location: </strong>For this position, we are open to hiring in Ann Arbor, MI 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> </p> <p>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: </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 matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures</li> <li>AD+D and Life Insurance </li> </ul> <p>At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical condi