Researcher – AI/ML Real-Time Embedded OS

Beaverbrook, Ottawa

On-site

Full-time

No salary posted1 weeks ago

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Employment type: Full-time · On-site
Posted: September 28, 2026
Province: Ontario (ON)

Hiring confidence: Sparse posting · 11/100

This posting is missing most of the signals we look for, or shows patterns common to listings that are not actively being filled. Check with the employer before applying. How this is scored

Job Overview

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Huawei Canada has an immediate permanent opening for a Researcher. About the team: The Intelligent Real-Time Operating System Lab focuses on OS architecture, concurrency challenges, and optimal resource management for diverse use cases such as the compute required for AI/ML. This lab aims to innovate operating system designs for mixed-criticality environments that exceed traditional methods. The focus of this lab is to develop next-generation OS platform support to enable high performance, maxi…

This role is based in Ontario. Huawei Technologies Canada Co., Ltd. is hiring for this full-time position through Jobily, where you can check how well your resume matches the posting before you apply.

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About this role in Ontario

Average salary for Researcher – AI/ML Real-Time Embedded OS in Ontario

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Typical qualifications for Canadian employers

Background in operating systems design and architecture
Knowledge of real-time and embedded systems
Understanding of AI/ML computational requirements
Experience with concurrency and resource management
Research experience in systems engineering

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What you'll do

Conduct research on OS architecture for mixed-criticality environments
Address concurrency challenges in real-time systems
Optimize resource management for AI/ML workloads
Develop next-generation OS platform designs
Innovate solutions for high-performance embedded systems
Collaborate with the Intelligent Real-Time Operating System Lab team
Contribute to advancing operating system research beyond traditional methods

What you'll need

Background in operating systems design and architecture
Knowledge of real-time and embedded systems
Understanding of AI/ML computational requirements
Experience with concurrency and resource management
Research experience in systems engineering
Strong problem-solving and analytical skills