Senior BEV & 3D Perception ML Engineer (Hybrid/Remote)

torcrobotics; Stati Uniti; Ibrido; USD 216.000 - 259.000; Tempo pieno

Vantaggi offerti da questo lavoro

Hybrid work in US

Remote options across the UnitedStates

Stock options

Bonus opportunity

401(k) with match

Descrizione del lavoro

TORC Robotics is seeking a Staff Machine Learning Engineer to lead BEV-based perception and multi-modal fusion for autonomous trucking. You will design cutting-edge models that fuse camera, LiDAR, radar, and maps into rich 3D representations.

The role emphasizes technical leadership, model innovation, and mature experimentation pipelines, with hybrid work options and strong compensation. You will mentor engineers and drive impactful research through deployment-ready systems.

Competenze

• 10+ years of deep learning for perception, 3D vision, or autonomous systems.
• MS or PhD in CS/EE/Robotics or equivalent practical experience.
• Expertise in BEV modeling and multi-view fusion.
• Strong background in camera-LiDAR fusion and multi-modal data.

Mansioni

• Define the technical roadmap for BEV-based perception models.
• Architect multi-modal networks for Camera, LiDAR, Radar, and HD map inputs.
• Build perception models using BEV transformers and voxel-based encoders.
• Own large-scale training pipelines: data sampling, augmentation, distributed training, hyperparameter tuning.
• Improve robustness for low visibility and occlusions.

Conoscenze

BEV modeling

3D scene understanding

multi-view fusion

Python

PyTorch

TensorFlow

distributed training

data pipelines

mentoring

ML model innovation

leading teams

Formazione

MS/PhD in CS/EE/Robotics or equivalent

Strumenti

Ray

Descrizione del lavoro

TORC Robotics is seeking a Staff Machine Learning Engineer to lead BEV-based perception and multi-modal fusion for autonomous trucking. You will design cutting-edge models that fuse camera, LiDAR, radar, and maps into rich 3D representations.

The role emphasizes technical leadership, model innovation, and mature experimentation pipelines, with hybrid work options and strong compensation. You will mentor engineers and drive impactful research through deployment-ready systems.