Engineering Manager, Active Sensors (LiDAR)
Torc RoboticsAnn Arbor, MI · Remote · full time · Management
Listed on Torc Robotics’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Lead the machine learning team building lidar and radar perception systems for autonomous trucks, managing both technical direction and people while balancing model performance against real-time compute constraints. Suits experienced ML managers comfortable with embedded systems complexity and collaborative cross-functional work.
Our summary, not Torc Robotics’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- Bachelor's degree in Computer Science, Robotics, Electrical Engineering, or related field with 6+ years of professional experience, or Master's degree with 4+ years
- 2+ years leading and managing engineers
- Strong technical foundation in machine learning and computer vision including 3D geometry and perception failure modes
- Production machine learning systems experience in autonomous driving, robotics, or real-world applications
- Experience with lidar sensing including scan patterns, reflectance, FMCW lidar, and sensor synchronization
- Machine learning lifecycle experience including data curation, model training, experimentation, evaluation, integration, and validation
- Python and PyTorch proficiency
- C++ production experience in perception or ML systems
- TensorRT experience for deep learning optimization
- Embedded computing platform understanding and real-time perception system constraints
- Technical roadmap definition and complex project planning across cross-functional dependencies
- Strong written and verbal communication skills
Nice to have
- PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or related field
- Experience with NVIDIA libraries and frameworks (CUDA, CuDNN, CuBLAS, NPP, custom TensorRT operations)
- Publications, patents, or open-source contributions in machine learning, computer vision, robotics, or autonomous driving