Torc Robotics builds self-driving software for heavy-duty freight trucks, and its stack shows an embedded-plus-ML profile: C++, ROS 2, Yocto and CUDA/TensorRT on NVIDIA hardware alongside PyTorch, Ray and Databricks for training. Senior-weighted, engineering-dominant hiring targets perception models, auto-labeling and an in-house data factory, while IBM DOORS and Jama Connect point to safety-grade requirements traceability.
Notable leadership hires: Engineering Director
Torc Robotics develops autonomous vehicle software for the trucking and freight industry, focused on highly automated Level 4 Class 8 trucks. The company was founded in 2005, is headquartered in Blacksburg, Virginia, and operates as a privately held subsidiary of Daimler following its 2019 acquisition. Its work spans perception, mapping, sensor integration and the full autonomous driving platform stack. Torc employs between 501 and 1,000 people and currently hires in the United States.
Torc uses C++, Python, ROS 2, Yocto, Bazel and CMake for vehicle software, NVIDIA CUDA, TensorRT and PyTorch for ML, plus Databricks, Spark, Ray and Apache Beam across AWS, GCP and Azure.
Job posts point to production ML perception models, bird's eye view perception, sensor integration for autonomous trucks, auto-labeling, an in-house annotation platform and a data ingestion and governance pipeline.
Yes. Engineering dominates Torc's open roles, skewed toward senior and staff levels, with smaller data, security and finance hiring, all in the United States, plus an Engineering Director search.
Other companies in the same industry, closest in size
Torc Robotics's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.
