🛠 Tech Stack

💼 About This Role

You'll lead BEV-based perception model development for Torc's autonomous driving stack. You'll drive architectural innovation and large-scale model training to advance spatial understanding from multi-modal sensor data. This role focuses on technical leadership in model innovation, not downstream integration.

🎯 What You'll Do

• Define technical roadmap for BEV perception models across detection, segmentation, road topology, and scene understanding.
• Design advanced multi-modal architectures fusing camera, LiDAR, radar, and HD map data.
• Own large-scale training workflows including data sampling, augmentation, distributed training, and hyperparameter optimization.
• Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer.

📋 Requirements

• 10+ years of experience in deep learning for perception, 3D vision, or autonomous systems.
• Proven expertise in BEV modeling, 3D scene understanding, and multi-view fusion.
• Strong background in multi-modal sensor fusion, particularly camera and LiDAR.
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.

✨ Nice to Have

• Experience with autonomous driving or robotics perception in production environments.
• Experience with MLOps and infrastructure tools (Ray).
• Track record of publications or open-source contributions in top-tier venues (CVPR, ICCV, NeurIPS, ICRA, CoRL).

🎁 Benefits & Perks

• 💰 Competitive compensation including bonus and stock options.
• 🏥 100% paid medical, dental, and vision premiums for full-time employees.
• 🏦 401K plan with 6% employer match.
• 🌴 Flexible schedule and generous paid vacation available immediately.
• 🏢 Company-wide holiday office closures.