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Torc Robotics

Autonomous truck software for Level 4

Staff Machine Learning Engineer - BEV/Multi-Modal Perception

Computer VisionConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 10 years of experience in deep learning for perception, 3D vision, and/or autonomous systems.
  • An M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field, or equivalent practical experience.
  • Proven expertise in BEV modeling, 3D scene understanding, and multi-view fusion.
  • A strong background in multi-modal sensor fusion, particularly integrating camera and LiDAR data.
  • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
  • Experience with large-scale data pipelines, distributed training, and experiment management systems.
  • Demonstrated leadership in driving ML model innovation and mentoring technical teams.

Responsibilities

  • Lead the development of BEV perception models across tasks such as detection, segmentation, road topology, and scene understanding, defining and executing their technical roadmap.
  • Design multi-modal architectures that fuse camera, LiDAR, radar, and HD map data into unified spatial representations.
  • Develop foundational perception models using BEV transformers, voxel-based encoders, or implicit scene representations.
  • Own large-scale training workflows, including data sampling strategies, augmentation pipelines, distributed training, and hyperparameter optimization.
  • Improve model robustness and generalization for long-tail conditions such as low visibility, occlusions, and rare scene configurations.
  • Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer performance.
  • Collaborate with sensor calibration, mapping, and fusion teams to ensure cohesive perception model interfaces.
  • Mentor and guide ML engineers in experimentation, code quality, and model validation.
  • Explore self-supervised learning, large-scale pretraining, and foundation models for 3D perception.

Desired Qualifications

  • Experience with autonomous driving or robotics perception in production environments.
  • Experience with MLOps and infrastructure tools such as Ray.
  • Hands-on expertise in BEV-based ML architectures, LiDAR-vision fusion, or spatial-temporal modeling.
  • Familiarity with 3D labeling, calibration, and sensor simulation pipelines.
  • A track record of publications or open-source contributions in venues such as CVPR, ICCV, NeurIPS, ICRA, or CoRL.
  • Understanding of performance tradeoffs and deployment constraints, including latency, memory, and accuracy.

About the Company

Torc Robotics

Autonomous truck software for Level 4

Torc Robotics builds software for autonomous trucks, aiming to enable Level 4 self-driving capabilities for freight transport. They develop driving systems that let heavy trucks operate autonomously under certain conditions, and they work with truck manufacturers and fleet operators to bring these solutions to market. The company integrates sensors from partners (such as Luminar Technologies) and provides ongoing updates and support to ensure reliability and performance. Unlike more general AV players, Torc focuses on commercial trucking and leverages strategic partnerships (for example with Daimler Trucks) to integrate its software into production vehicles and fleets. Its goal is to improve road safety and freight efficiency by deploying scalable, commercial autonomous trucking solutions.

Company size
501-1,000
Company stage
M&A
Total funding
Not listed
Headquarters
Blacksburg, VA
Founded
2005

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