Senior, ML Engineer - 3D Reconstruction

About the Company At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. 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. Meet The Team: The Pseudo-Labeling team's goal is to create high-quality annotations on sensor data (images, point clouds). The annotations include 2D, 3D bounding boxes, classes, trajectories, lane lines, segmentations, depths, and high-definition map elements. The annotations are then used by different downstream users — for example, perception teams use them to train various models, mapping teams use them to build and maintain HD maps, and simulation teams use them for generating new data. This role owns the hardest problems in the team's lane line and mapping stack and is expected to set technical direction across lane line reconstruction, map creation, and pose accuracy. What You’ll Do: Own the design, implementation, and deployment of offline 3D reconstruction, lane line [... source excerpt omitted ...] cets of project execution. Stay ahead of the latest developments in AI and ML for autonomous driving, 3D reconstruction, and automated mapping, and bring emerging techniques into production. Independently develop offline perception and mapping models or algorithms using disciplined software development processes, making recommendations for developing new code or re-using existing code, implementing version control, and maintaining documentation of created applications. Define and implement ingestion, data preparation, curation, and governance of large, multi-faceted data sets supporting analytics models and workflows. Proactively assess current capabilities to identify areas fo [... source excerpt omitted ...] including quantifying the impact of pose and calibration error on downstream quality. Guide and produce information products, supporting visualization and data accessibility in a customer-centric manner. Evaluate and make recommendations regarding technical advances that improve productivity and quality, reduce flow times, and enhance operational surety. Develop guidelines and standards for analytics and machine learning models, their deployment, and associated processes. Provide technical guidance, technical leadership, coaching and mentoring to team members. What You’ll Need to Succeed: Considered an expert and highly skilled in discipline; conducts highly complex, import