Find work in Canada.
665,406 jobs across our Canadian network. How we count
Jobs in Canada
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Senior Consultant - Risk Data & Technology - Data Engineer
Deloitte
Hands on development experience is important and should be well versed with python/pyspark.
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Senior AI Engineer. Innovation and R&D
Equinix
Proficiency in Python and PyTorch, and with Hugging Face tooling
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Machine Learning Software Developer, In-Vehicle Infotainment
Ford Motor Company
Ford’s Electric Vehicles, Digital and Design (EVDD) team is charged with delivering the company’s vision of a fully electric transportation future. EVDD is customer-obsessed,…
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Lead ML Engineer – Classical ML & GenAI/RAG
Delaplex
The ideal candidate will have a strong foundation in classical Machine Learning/Data Science, with substantial hands-on experience building ML solutions before the recent GenAI wave, and…
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Financial Services - Principal Architect
Talentmatics
…and engineering teams. The individual will remain hands-on with architecture design, technical evaluations, proof of concepts, and code-level…
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Principal Software Development Engineer
Advanced Micro Devices, Inc
…working across multiple layers of the software stack in both Python and C++. They should be able to communicate effectively and work well with different teams across AMD and with…
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Data Architect - Calgary
Slalom
Slalom is a fiercely human business and technology consulting company that leads with outcomes to bring more value, in all ways, always. From strategy through delivery, our agile teams…
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Senior Technical Analyst - DevOps & Production Ops
Randstad Digital
Our client is seeking a hands-on Senior Technical Analyst / Developer with a strong focus on AWS DevOps, cloud infrastructure, and production operations to deploy, scale, and support…
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Ingénieur ( e) de données- Data Engineer
Klever
Collaborate with cross-functional teams, including data scientists, domain experts, and software engineers, to understand data requirements and provide the necessary infrastructure and…
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Applied AI/ML Scientist
lululemon
Experience with ML implementation using commonly used tools such as Python, pyTorch, cloud ML platforms and libraries, open-source toolkits.
