Staff Machine Learning Engineer – E2E

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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 the design and development of E2E models, defining architectures that directly map multimodal sensor inputs (camera, LiDAR, radar, HD maps) to driving actions or mid- to high-level cost/objective functions. • Lead large-scale training and evaluation for E2E learning, integrating data from perception, behavior prediction, and control systems. • Develop and refine learning objectives aligned with real-world driving criteria: safety, comfort, compliance, and efficiency. • Build scalable pipelines for multitask, multimodal learning, leveraging both real-world and synthetic data. • Prototype and evaluate new paradigms such as differentiable planning, imitation learning, reinforcement learning, and world models for autonomous vehicle behavior. • Collaborate cross-functionally with Perception, Prediction, and Motion Planning teams to align interfaces and ensure consistency between learned and modular components. • Establish robust evaluation frameworks for E2E performance, including closed-loop simulation and on-road validation. • Mentor engineers and scientists in large-scale experimentation, model interpretability, and data-driven debugging. • Stay at the forefront of machine learning research, exploring advances in foundation models, sequence modeling, self-supervision, and generative world representations.

🎯 Requirements

• Master’s or PhD in Computer Science, Electrical Engineering, Robotics, or a related field (or equivalent practical experience) • 10+ years of experience developing deep learning models for perception, planning, or control. • Deep expertise in multimodal machine learning, sequence modeling, or policy learning (e.g., Transformers, diffusion models, imitation learning). • Proven experience training and optimizing large-scale models for real-world tasks. • Strong skills in Python, PyTorch or TensorFlow, and experience with distributed machine learning application frameworks. • Solid understanding of sensor fusion, spatio-temporal modeling, and vehicle dynamics. • Demonstrated leadership in driving technical roadmaps, mentoring teams, and delivering production-quality ML solutions. • Experience using Ray

🏖️ Benefits

• Competitive compensation program including bonus component and stock option grants • Medical, dental, and vision coverage for full-time employees • Retirement savings plan (RRSP) with a 4% employer contribution • Public transit subsidy (Montreal area only) • Flexible working hours and generous paid time off • Company-wide office closures during major holidays • Life insurance