Torc Robotics
Engineering Manager, Active Sensors (LiDAR)
Remote, U.S, Ann Arbor, MI, Fort Worth, TX, Blacksburg, VA +1 · Remote · Manager · Full-time · Posted Oct 8, 2026
- Location
- Remote, U.S, Ann Arbor, MI, Fort Worth, TX, Blacksburg, VA
Ann Arbor, Michigan, United States - Experience
- 6+ years with a bachelor's degree, or 4+ years with a master's degree; 2+ years leading and managing engineers.
- Education
- Bachelor's degree in Computer Science, Robotics, Electrical Engineering, or related field, or a master's degree.
About the job
Leads the team developing and deploying lidar- and radar-based perception systems for autonomous trucks, including technical direction, people management, and delivery across the machine learning lifecycle.
What you'll do
- Lead, coach, hire, and develop machine learning and software engineers.
- Set the active-sensor perception roadmap and guide development of multitask models for object detection, road and lane detection, and free-space estimation.
- Own lifecycle delivery, evaluation, integration, release, and cross-functional coordination.
What they ask for
- Bachelor's degree in Computer Science, Robotics, Electrical Engineering, or related field with 6+ years of professional experience, or a master's degree with 4+ years of experience.
- 2+ years of experience leading and managing engineers.
- Experience developing and deploying production machine learning systems, with a strong foundation in machine learning, computer vision, and lidar sensing.
- Strong proficiency in Python and PyTorch, practical production experience with C++, and experience deploying and optimizing deep learning models using TensorRT.
Nice to have
- PhD in a related field.
- Experience with NVIDIA libraries and frameworks, custom TensorRT operations, or relevant publications, patents, or open-source contributions.
Tools
Python, PyTorch, C++, TensorRT, CUDA, CuDNN, CuBLAS, NPP
AI focus
Develops production machine-learning perception for autonomous trucks, including multitask lidar and radar models, sensor fusion, robustness, and real-time embedded deployment.
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