Software Engineer II - Fleet Enablement & Insights (Annotation Platform)
Torcrobotics · Ann Arbor, MI, Fort Worth, TX, Blacksburg, VA
About this role
## Software Engineer II — Fleet Enablement & Insights (Annotation Platform) ### About Torc Torc believes 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 its solutions with experienced partners. Now part of the Daimler family, Torc focuses on developing software for automated trucks to transform how the world moves freight. ### Meet the Team You’ll join the **Fleet Enablement & Insights** team to build Torc’s in-house **annotation platform**—web-based tooling that turns multi-sensor autonomy data into labeled datasets used to train and validate the autonomous truck platform. You’ll develop an interactive **2D/3D annotation editor** and the services behind it, including fusing **HD map data** with **multi-camera, lidar, and other sensor context** into the labeling workflow. The platform also supports adjacent use cases such as **data QC** and **scene-selection review**. ### What You’ll Do - Design, develop, and maintain the **TypeScript/React** web application for 2D/3D annotation (cuboid/polygon editing, cross-frame interpolation & track propagation, attribute editing, and review-first workflows). - Build high-performance **point cloud and image rendering** with **three.js/WebGL** (octree/LOD streaming, predictive prefetching for smooth scrubbing, camera–LiDAR projection, multi-sensor overlays). - Build backend services behind the editor: label storage & versioning, task assignment & QA workflow, authentication, and multi-user isolation guardrails. - Integrate **pre-labeling/pseudo-labeling** outputs into the annotation workflow and instrument acceptance-rate/throughput metrics to improve the auto-labeling feedback loop. - Fuse **HD map data** into annotation and QC workflows as priors/reference layers. - Build data converters and ingestion paths from Torc multi-sensor scene data (multiple LiDARs, many cameras, calibration data) into platform formats. - Deliver dataset exports compatible with downstream ML training/validation, including lineage and auditability required for the safety case. - Use **AWS** services and **Databricks adjacency** to host scene data and deploy scalable services. - Collaborate with Data Annotation, Autonomy/ML, Scene Selection, Mapping, and Data Engineering to align with real annotator workflows and downstream requirements. - Participate in agile ceremonies, sprint planning, and weekly demos with annotators and stakeholders. - Contribute to engineering excellence via code reviews, documentation, and knowledge sharing; harden prototypes into production. - Identify and address technical debt, performance bottlenecks, and reliability gaps. ### What You’ll Need to Succeed - Strong proficiency in **TypeScript** and **React**, shipping production-quality web applications. - Experience with **browser-based 3D graphics** (three.js/WebGL or similar) or strong graphics fundamentals with the ability to ramp quickly. - Proficiency in **Python** for production backend services and APIs. - Experience working with **large sensor datasets** (point clouds, imagery, video) and optimizing data-heavy UIs. - Strong **SQL** skills and hands-on experience with **PostgreSQL** for label/task/metadata storage. - Experience with **AWS** for hosting data and deploying services. - Proficiency with **Git/GitHub** for version control and collaborative workflows. - Familiarity with **JIRA** (or similar) for t
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