Senior BEV & Multi-Modal Perception ML Lead

torcrobotics; United States; Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Bonus + stock options

Medical, dental, vision covered

401K with 6% match

Flexible schedule & vacation

Company holidays

Job summary

Torc is seeking a Staff Machine Learning Engineer focused on BEV and multi-modal perception to lead model innovation for autonomous trucking perception. You will guide architecture, large-scale training, and data-driven improvements within Torc's perception stack.

Required are 10+ years in deep learning for perception and a strong background in BEV, 3D vision, and sensor fusion, with leadership experience and proficiency in Python and DL frameworks. Hybrid work options available in the US.

Qualifications

• 10+ years of experience in deep learning for perception, 3D vision, and autonomous systems.
• MS or PhD in Computer Science, Electrical Engineering, Robotics, or related field (or equivalent practical experience).
• Proven expertise in BEV modeling, 3D scene understanding, and multi-view fusion.
• Strong background in multi-modal sensor fusion, especially camera and LiDAR.
• Proficiency in Python and DL frameworks (PyTorch, TensorFlow).
• Experience with large-scale data pipelines, distributed training, and experiment management systems.
• Demonstrated leadership in ML model innovation and mentoring teams.

Responsibilities

• Lead BEV model development and set the technical roadmap for BEV-based perception models.
• Design multi-modal architectures that fuse camera, LiDAR, radar, and HD maps into unified representations.
• Develop foundation perception models using BEV transformers, voxel encoders, or implicit scene representations.
• Own large-scale training workflows from data sampling to distributed training and hyperparameter optimization.
• Improve robustness and generalization for challenging conditions and diverse environments.
• Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer.
• Collaborate with sensors calibration, mapping, and fusion teams to ensure cohesive interfaces.
• Mentor ML engineers and promote best practices in experimentation and validation.
• Stay at the forefront of ML research with self-supervised learning and foundation models.

Skills

Deep learning

BEV modeling

3D vision

Sensor fusion

MLOps

Python

PyTorch

TensorFlow

Leadership

Education

MS/PhD in CS/EE/Robotics or equivalent

Tools

PyTorch

TensorFlow

Ray

Python

Job description

Torc is seeking a Staff Machine Learning Engineer focused on BEV and multi-modal perception to lead model innovation for autonomous trucking perception. You will guide architecture, large-scale training, and data-driven improvements within Torc's perception stack.

Required are 10+ years in deep learning for perception and a strong background in BEV, 3D vision, and sensor fusion, with leadership experience and proficiency in Python and DL frameworks. Hybrid work options available in the US.