ML / AI Jobs in Canada
There are 574 open ML / AI jobs in Canada on freehire right now. 185 of them were posted recently. The skills employers ask for most often are machine-learning, ai and python.
Salary
| Currency | Period | 25th | Median | 75th | Postings |
|---|---|---|---|---|---|
| CAD | year | CA$151,700 | CA$184,000 | CA$213,012 | 127 |
| USD | year | $178,500 | $200,000 | $227,400 | 17 |
From postings that disclose pay. Currencies are counted separately, never converted.
Most requested skills
- machine-learning 97%
- ai 84%
- python 72%
- pytorch 44%
- cloud 44%
- llm 33%
- deep-learning 33%
- tensorflow 30%
How the work is done
- Remote 100 · 17%
- Hybrid 78 · 14%
- Onsite 14 · 2%
Visa sponsorship offered in 68% of the 90 postings that state a position on it.
Seniority
- Senior 169
- Staff 46
- Lead 39
- Principal 22
- Intern 18
- C-level 8
Who is hiring
- 1000+ employees 161
- 501-1000 employees 40
- 51-200 employees 9
- 11-50 employees 8
- 201-500 employees 4
- 1-10 employees 2
Senior Applied AI/ML Developer
Build and deploy NLP and ML models to enhance Autodesk’s RAG platforms, leading ML initiatives and mentoring teammates.
Staff Machine Learning Engineer - News, Books, and Stocks Team
Build and deploy ML models for Apple News, Books, and Stocks to power recommendations, search, and AI features using Python, PyTorch, and TensorFlow.
Machine Learning Engineer, VLA & RL - Senior
Build vision-language-action and reinforcement learning models for real-world robotic systems, training policies that generalize across hardware and deployments.
Junior ML Engineer: AI, LLMs & Cloud Pipelines
Build, deploy, and maintain AI/ML models including LLMs and agentic systems to power scalable products and workflows.
Dubai - Head of Machine Learning & AI
Lead a team to build and deploy ML, ML Ops, and Generative AI systems that power AI-driven products and platforms at scale.
Senior Machine Learning Developer - Commerce AI
Build and maintain scalable ML systems for enterprise commerce clients, focusing on reliability, low-latency inference, and MLOps best practices using Python, PyTorch, AWS, and Kubernetes.
Research Scientist - AI/ML
Research Scientist driving novel AI/ML and computer vision methods, publishing at top conferences, and collaborating with engineering to scale solutions for a large userbase.
Staff AI/ML Product Manager
Lead AI/ML product development for an insurance-focused platform, owning ML features that automate renewals and drive data-driven insights for brokerages.
Principal AI/ML Architect
Principal AI/ML Architect designs and advises on production ML systems, MLOps/LLMOps pipelines, and GenAI architectures on AWS for enterprise clients, translating technical depth into business value.
Senior Machine Learning / Computer Vision Applied Scientist
Build and deploy 4D Vision™ systems for industrial robots, extending object detection, depth estimation, and pose estimation using PyTorch and foundation models to enable precise automation on factory floors.
Staff Developer - AI/ML
Lead Benevity’s AI/ML strategy, designing scalable GenAI systems, LLM-powered features, and MLOps pipelines to deliver measurable business value from model training to production monitoring.
Staff Software Engineer (Machine Learning Platform)
Lead the design and architecture of Stripe’s ML Platform, building scalable systems for training, serving, and monitoring ML models that power fintech products like Payments and Radar.
Senior Machine Learning Engineer, Recommendations
Build and deploy ML models for real-time ride-sharing recommendations using deep learning frameworks like PyTorch or TensorFlow.
Staff Machine Learning Engineer, Supply
Lead the ML vision for Lime’s supply and fleet optimization systems, building forecasts and deployment strategies that power millions of rides worldwide.
Senior Machine Learning Engineer
Build and scale a machine-learning platform that accelerates drug discovery, enabling the full ML lifecycle from development through deployment.
Machine Learning Engineer (Chat Agent)
Build and deploy cutting-edge ML/NLP models (LLMs, transformers) to power real-time call-center coaching, using Python, PyTorch, and cloud infra.