Senior Machine Learning Engineer developing deep learning models for camera-based perception in autonomous trucks. Working closely with cross-functional teams to ensure model integration and performance.
Responsibilities
Design, develop, and deploy deep learning models for camera-based perception (e.g., object detection, segmentation, depth estimation, scene understanding)
Own end-to-end model development for scoped areas, from data curation and training to evaluation and deployment
Write production-quality ML code to support scalable training, evaluation, and inference pipelines
Analyze model performance across diverse driving scenarios, identify failure modes, and improve robustness and generalization
Contribute to and improve large-scale training pipelines, including dataset preparation, distributed training, and experiment tracking
Partner with data teams to improve dataset quality, including labeling strategies and coverage of edge cases
Collaborate with perception, simulation, and validation teams to evaluate and integrate models into the autonomy stack
Improve tooling, workflows, and infrastructure to accelerate experimentation and model iteration
Contribute to model architecture decisions and technical discussions within the team
Mentor junior engineers on implementation, debugging, and best practices
Requirements
Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 6+ years of industry experience, OR Master’s degree with 3+ years OR PhD with 1+ years of experience
Experience developing and deploying deep learning models for computer vision or perception systems
Strong programming skills in Python and PyTorch, with experience writing production-quality ML code
Experience training and evaluating models using large-scale datasets and distributed compute environments
Solid understanding of modern deep learning architectures used in perception (e.g., CNNs, transformers, 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 collaborating cross-functionally to integrate ML models into larger autonomy or robotics systems
Benefits
A competitive compensation package that includes a bonus component and stock options
Medical, dental, and vision for full-time employees
RRSP plan with a 6% employer match
Public Transit Subsidy (Montreal area only)
Flexibility in schedule and generous paid vacation
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