Senior Machine Learning Engineer – Camera Model

This is a fully remote position, open to applicants in Canada.

📋 Description

• Develop and implement machine learning models for camera-based perception in autonomous trucks, encompassing object detection, segmentation, depth estimation, and scene comprehension.

• Take ownership of the entire model development process, from data curation and training to evaluation and deployment.

• Produce production-quality machine learning code for scalable training, evaluation, and inference pipelines.

• Assess model performance across varied driving situations, identify failure modes, and enhance robustness and generalization.

• Refine large-scale training pipelines, which include dataset preparation, distributed training, and experiment tracking.

• Collaborate with data teams to ensure dataset quality, labeling strategies, and edge-case coverage.

• Work closely with perception, simulation, and validation teams to integrate models into the autonomy stack.

• Enhance tools, workflows, and infrastructure for experimentation and model iteration.

• Participate in model architecture decisions and engage in technical discussions.

• Guide junior engineers on implementation, debugging, and best practices.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical discipline with 6+ years of industry experience, OR a Master’s degree with 3+ years OR a PhD with 1+ years of experience.

• Proven experience in developing and deploying deep learning models for computer vision or perception systems.

• Strong programming proficiency in Python and PyTorch, with a background in writing production-quality machine learning code.

• Experience in training and evaluating models using large datasets and distributed computing environments.

• Comprehensive understanding of contemporary deep learning architectures employed in perception, including CNNs, transformers, and multi-task models.

• Experience in debugging model behavior, analyzing performance metrics, and enhancing model reliability.

• Capability to translate ambiguous challenges into structured machine learning solutions and work independently.

• Experience in cross-functional collaboration to integrate machine learning models into broader autonomy or robotics systems.

• Bonus: Experience in autonomous driving, robotics, or simulation-based machine learning systems.

• Bonus: Familiarity with multi-task learning or unified perception architectures.

• Bonus: Experience with large-scale data pipelines, distributed training systems such as Ray, or experiment management frameworks.

• Bonus: Knowledge of camera calibration, geometric reasoning, or 3D perception from images, including BEV, monocular depth, and structure-from-motion.

• Bonus: Experience in deploying machine learning models into production or real-world robotics systems.

🏝️ Benefits

• A competitive compensation package that includes 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 (available for the Montreal area only).

• Flexible scheduling and generous paid vacation.

• Company-wide holiday office closures.

• Life Insurance.

• Potential sign-on bonuses, relocation assistance, and other forms of compensation may be included in the total compensation package.