Applied ML Engineer working on AI - driven insights at Kaseya. Collaborating with product teams to enhance features with machine learning and data analysis.
About the role
- 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
- Company-wide holiday office closures
- Life Insurance
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
Adversarial Machine Learning Engineer conducting adversarial testing and simulations on LLM - driven AI systems for enterprise security. Collaborating with teams to validate and document findings.
MLOps Engineer managing infrastructure for large 2D and 3D media datasets at NBCUniversal. Responsible for automation, reproducibility, and performance of machine learning lifecycles.
Senior ML Engineer leading the strategic direction of machine learning infrastructure for global food delivery platform. Collaborating with Data Science team for seamless model deployment and innovation.
Machine Learning Intern/Co - op at Cohere working on developing and training models for AI applications. Join a team focused on advancing AI technology in an inclusive environment.
Machine Learning Engineer designing and deploying detection ML systems for social engineering defense platform at Doppel. Collaborating to mitigate evolving digital threats using AI.
Senior Software Developer responsible for designing and developing solutions in data engineering and machine learning. Collaborating with teams to deliver scalable software solutions with agile methodologies.
Senior ML Engineer responsible for designing and building ML pipelines for a Trust Scoring platform. Involves productionizing models and implementing MLOps best practices.
Principal Machine Learning Engineer designing the core ML systems for AI agents at Workday. Collaborating in cross - functional teams to integrate ML solutions into the platform.
Staff Machine Learning Research Developer at D - Wave enabling quantum machine learning methods. Researching and developing software to enhance quantum computing capabilities for optimization and AI.