Senior Engineer – Machine Learning, Offline Perception

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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

• Design, implement, test, and deploy offline object detection, tracking, and fusion modules to automatically generate annotations on cloud services from recorded sensor data (cameras, lidars, radars) • Demonstrated project management skills, acting as a project lead guiding a team whose members have limited experience across multiple aspects of project execution • Stay current with the latest developments in AI and machine learning for autonomous driving • Independently develop models or algorithms for offline perception • Document created applications • Define and implement ingestion, preprocessing, curation, and governance of large, multidimensional datasets to support models and analytical workflows • Proactively assess current capabilities to identify areas for improvement and propose solutions aligned with core strategy and operations • Measure and monitor the quality of automatic labeling to meet internal customer requirements • Guide and produce insights, supporting data visualization and accessibility in a customer-focused manner • Evaluate and recommend technical advances that improve productivity and quality, reduce time-to-delivery, and strengthen operational reliability • Develop guidelines and standards for analytical and machine learning models, their deployment, and associated processes • Provide technical guidance or business-process expertise, technical leadership, coaching, and mentorship to team members.

🎯 Requirements

• Considered highly skilled and competent in their discipline; performs complex, impactful work with minimal supervision and significant latitude for independent judgment • Scope of influence: Expected to drive alignment between the team’s interfaces and the rest of the organization. Designs, maintains, and owns the team’s technical solutions and fosters consensus. Mentors and guides engineers within the group • Bachelor's degree in Computer Science, Robotics, Electrical Engineering, or a related technical field, plus demonstrated technical skills and aptitude generally gained through more than 6 years of experience OR; • Master’s degree in Computer Science, Robotics, Electrical Engineering, or a related technical field, demonstrating technical skills and knowledge generally gained through more than 3 years of experience OR; • PhD in Computer Science, Robotics, Electrical Engineering, or a related technical field, along with demonstrated technical skills and mastery, generally gained after more than 1 year of experience • Required qualifications (a combination of the following skills): active learning and pseudo-labeling – computer vision, deep learning, model training • Two of the following: 2D/3D object detection, tracking, sensor fusion, semantic segmentation, SLAM, BEV • Large-scale machine learning operations and tooling (MLOps) – ML frameworks, experiment tracking, model registry, MLflow, Weights & Biases, ML metrics and evaluation/quality • Distributed machine learning frameworks – PyTorch, Lightning, Ray • Model data curation – data processing with Parquet (PyArrow, Daft, Pandas, etc.) • Development tools and ecosystem (at scale) – strong software development skills in Python. Also experience with VDI and cloud development environments, continuous integration systems (GitHub Actions), and Docker.

🏖️ Benefits

• Competitive compensation package including bonus components 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 region only) • Flexible scheduling and generous paid time off • Company-wide office closures for statutory holidays • Life insurance