Senior, Machine Learning Engineer

Responsibilities

• Design, develop, and deploy deep learning models for camera-based autonomous-vehicle perception.
• Own model development from data curation and training through evaluation and deployment.
• Build production-quality ML code and scalable training, evaluation, and inference pipelines.
• Analyze model performance and failure modes across diverse driving scenarios to improve robustness and generalization.
• Improve dataset quality, labeling strategies, distributed training, experiment tracking, tooling, and experimentation workflows.
• Collaborate with perception, simulation, data, infrastructure, and validation teams to integrate models into the autonomy stack.
• Contribute to model architecture and technical decisions.
• Mentor junior engineers on implementation, debugging, and engineering practices.

Requirements

• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field and 6+ years of industry experience, or a master’s degree and 3+ years of experience, or a PhD and 1+ years of experience.
• Experience developing and deploying deep learning models for computer vision or perception systems.
• Strong programming skills in Python and PyTorch, including production-quality ML code.
• Experience training and evaluating models with large-scale datasets and distributed compute environments.
• Understanding of modern deep learning architectures such as CNNs, transformers, and multi-task models.
• Experience debugging model behavior, analyzing performance metrics, and improving model reliability.
• Ability to translate ambiguous problems into structured ML solutions and deliver independently.
• Experience integrating ML models into larger autonomy or robotics systems.
• Preferred experience includes autonomous driving, robotics, simulation-based ML, multi-task or unified perception architectures, large-scale data pipelines, Ray, experiment management frameworks, camera calibration, geometric reasoning, BEV, monocular depth, structure-from-motion, and production or real-world robotics deployment.

Benefits

• Competitive compensation package with a bonus component and stock options.
• Medical, dental, and vision coverage for full-time employees.
• RRSP plan with a 6% employer match.
• Public transit subsidy for the Montreal area.
• Flexible schedule and generous paid vacation.
• Company-wide holiday office closures and life insurance.
• Hiring is available in Montreal, Canada, or remotely within Canada.