torcrobotics
Software for autonomous heavy-duty trucking.
Company facts
- Founded
- 2005
- Employees
- 867
- Headquarters
- United States
- CEO
- Peter Vaughan Schmidt
- Type
- Private
- Funding
- Corporate Round · 2019
- Subsidiaries
- Algolux, Torc Europe GmbH
About
What began in 2005 as Torc Technologies, a venture by a group of Virginia Tech graduate students, has evolved into a leading name in autonomous vehicle technology. The mission from the outset was to continue their collegiate work on autonomous vehicle software, initially focusing on Tele-Operated Robotic Controls (TORC) and developing Level 4 autonomous technology. A significant early milestone came in 2007 when Torc, in partnership with Virginia Tech, secured third place in the DARPA Urban Challenge. This achievement involved their Ford Escape, 'Odin,' autonomously navigating 60 miles of urban and off-road environments. The company's journey continued with impactful projects, including a 2010 partnership with Virginia Tech for the National Federation of the Blind's Blind Driver Challenge, which earned them the National Instruments' 2010 Application of the Year. This project saw a blind driver independently operate Torc's modified Ford Escape on the Daytona Speedway in 2011. Torc's expertise also extended to defense, developing autonomous solutions like the Ground Unmanned Support Surrogate (GUSS) to assist military personnel. Over the years, Torc has been involved in various defense and heavy equipment applications, and participated in the DARPA Robotics Challenge. A pivotal moment arrived in March 2019 when Daimler AG, through Daimler Trucks North America, acquired a majority stake in Torc Robotics. This partnership shifted Torc's primary focus to commercializing autonomous trucks for long-haul applications in the United States. Torc is now an independent subsidiary of Daimler Truck AG. The company has since expanded its operations, opening an engineering office in Austin, Texas, and a Technology and Development Center in Stuttgart, Germany in 2022, as well as facilities in Albuquerque, New Mexico, and Montreal, Canada. Torc continues to advance its 'physical AI,' enabling self-driving trucks to perceive, understand, and act in the real world, with a commercial launch targeted for 2027.
Software Engineer, II - Map Enablement
Senior software engineer on Torc's Map Enablement team, designing and scaling mapping data processing pipelines and routing/navigation systems for autonomous trucks. Day-to-day involves building high-throughput pipelines and APIs, mainly in Python (C++ also used) on AWS, working with loosely defined requirements.
HiL V&V Manager
What you will do: As the HiL Test Manager, you will lead a team of HiL test engineers responsible for the hardware-in-the-loop verification and validation (V&V) of Torc’s autonomous truck. You will own the HiL test…
Staff Systems Engineer
Staff Systems Engineer at Torc Robotics leads the Metrics for Release and Hardware-in-the-Loop (HiL) groups, architecting scalable platforms to validate self-driving software — orchestrating distributed compute, telemetry pipelines, and requirements traceability — using Python, C++, ROS, CAN networking, and systems engineering tools like Jama and Cameo.
Engineering Manager, Active Sensors (LiDAR)
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…
ML Engineer, II - App Engine
Develops a C++ SDK/framework for composing and running autonomous-truck software on embedded Nvidia devices, focusing on performance, safety, and resource constraints.
Staff, Software Engineer - Motion Planning (Unstructured Environments)
Leads development of motion planning algorithms for autonomous trucks, designing trajectory generation and optimization systems in C++ on Linux to ensure safe navigation in unstructured environments.
Senior, Machine Learning Engineer - 3D Perception
Senior Machine Learning Engineer designing and deploying 3D perception models for autonomous trucks, using PyTorch and multi-modal sensor data to improve environmental understanding.
Machine Learning Engineer, II - 3D Perception
Build and improve 3D perception models (LiDAR, cameras) for autonomous trucks using PyTorch and Python, integrating ML into Torc’s autonomy stack.