Staff Machine Learning Engineer – BEV

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Torc Robotics

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Transport • Hardware • Artificial Intelligence

Torc Robotics is an innovative company focused on commercializing self-driving trucks for long-haul freight transportation. As an independent subsidiary of Daimler Truck, the company is developing autonomous technology, primarily focusing on the Freightliner Cascadia. Torc is committed to safe transportation, continuously improving its solutions through rigorous testing and integration of industry-leading sensors. It collaborates with fleet management companies to deploy real-world autonomous solutions, aiming to lead the industry in autonomous trucking.

501 - 1000 employees

Founded 2007

🚗 Transport

🔧 Hardware

🤖 Artificial Intelligence

📋 Description

• Lead BEV model development: define and execute the technical roadmap for BEV-based perception models across multiple tasks (e.g., detection, segmentation, road topology and scene understanding). • Design advanced multimodal architectures that fuse heterogeneous sensor data (camera, LiDAR, radar, HD maps) into unified spatial representations. • Develop foundational perception models leveraging BEV transformers, voxel-based encoders, or implicit scene representations. • Own large-scale training workflows, from data sampling strategies and augmentation pipelines to distributed training and hyperparameter optimization. • Improve model robustness and generalization, accounting 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. • Work cross-functionally with sensor calibration, mapping, and fusion teams to ensure cohesive perception model interfaces. • Mentor and guide machine learning engineers, cultivating best practices in experimentation, code quality, and model validation.

🎯 Requirements

• Master’s degree or PhD in computer science, electrical engineering, robotics, or a related field (or equivalent practical experience). • 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 experience in multimodal 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 innovation in machine learning models and mentoring technical teams.

🏖️ Benefits

• Competitive compensation program including bonus components and stock option grants • Medical, dental, and vision coverage for full-time employees • Registered Retirement Savings Plan (RRSP) with a 4% employer contribution • Transit subsidy (Montreal region only) • Flexible work hours and generous paid vacation • Company-wide office closures during holidays • Life insurance