Senior Machine Learning Engineer – Camera Model

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

📋 Description

• Design, create, and implement deep learning models for camera-based perception tasks such as object detection, segmentation, depth estimation, and scene understanding.

• Take ownership of the complete model development process for defined areas, encompassing data curation, training, evaluation, and deployment.

• Develop production-grade ML code to facilitate scalable training, evaluation, and inference pipelines.

• Evaluate model performance across various driving scenarios, identify potential failure modes, and enhance robustness and generalization.

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

• Collaborate with data teams to elevate dataset quality, focusing on labeling strategies and coverage of edge cases.

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

• Enhance tools, workflows, and infrastructure to expedite experimentation and model iteration.

• Participate in model architecture decisions and engage in technical discussions within the team.

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

⛳️ Requirements

• A Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with over 6 years of industry experience, OR a Master’s degree with more than 3 years, OR a PhD with at least 1 year of experience.

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

• Strong programming capabilities in Python and PyTorch, with a background in writing production-quality ML code.

• Experience in training and evaluating models utilizing large-scale datasets and distributed computing environments.

• A solid grasp of modern deep learning architectures applicable to perception, including CNNs, transformers, and multi-task models.

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

• Ability to convert ambiguous problems into structured machine learning solutions and deliver independently.

• Experience in cross-functional collaboration to integrate ML models into broader autonomy or 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 (Montreal area only).

• Flexible scheduling and generous paid vacation.

• Company-wide holiday office closures.

• Life Insurance.