Software engineer jobs in Canada

Find software engineer jobs across Canada. Choose a place, compare current openings and read the employer’s requirements.

Counted Sep 21, 2026

Hiring at a glance

View jobs

Open jobs: 2,190
Employers: 920

Advertised starting pay

Average starting payCAD / year: $128,199Across 275 listings
Average starting payUSD / year: $149,896Across 97 listings
Average starting payCAD / hour: $55.83Across 28 listings

Employer-advertised starting pay, not employee salaries. Currencies and pay periods stay separate.

Where work happens

Remote: 12%258 listings
Hybrid: 41%895 listings
On-site: 46%1,001 listings

Not specified: 2% (36 listings)

Employers hiring include Amazon (97), Arista Networks (38), EA SPORTS (27).

Sources & calculation notes

These figures describe the listings on this role page at the date shown, not the whole job market. Listings can change.

Employer-listed minimums from at least 10 listings per currency and pay period. These are advertised starting amounts, not employee salaries. Jobs without a minimum and unusual amounts are excluded.

Hybrid and on-site classifications may be inferred from descriptions. Check the original ad. How we count

Software engineer jobs in Canada

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Huawei Canada
Markham, ON
Full-time
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Cerebras

Cluster Operations Software Engineer

Toronto, ON, Canada

Job type: Full-time
Experience: 6-8 years of relevant experience in managing and operating complex compute infrastructure, preferably in the context of machine learning or high-performance computing.
Posting language: English
Posted: Aug 13, 2026

Apply About employer

Applications open in a new tab.

Original job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.

This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

The Role

We are seeking a highly skilled and experienced AI Cluster Operations Engineer to manage and operate our cutting-edge machine learning compute clusters. These clusters would provide the candidate with an opportunity to work with the world's largest computer chip, the Wafer-Scale Engine (WSE), and the systems that harness its unparalleled power.

You will play a critical role in ensuring the health, performance, and availability of our infrastructure, maximizing compute capacity, and supporting our growing AI initiatives. This role requires a deep understanding of Linux-based systems, containerization technologies, and experience with monitoring and troubleshooting complex distributed systems. The ideal candidate is a proactive problem-solver with expertise in large-scale compute infrastructure, dependable and an advocate for customer success.

Responsibilities

Deploy, configure, and debug container-based services using Docker.
Build and own software solutions that power cluster operations, including monitoring platforms, workflow automation systems, operational dashboards, and reliability tooling.
Collaborate with cross-functional teams to translate operational requirements into scalable O&M products and platform capabilities.
Develop APIs, automation services, and integrations that improve operational visibility, incident response, and fleet management across global AI infrastructure.
Manage and operate multiple advanced AI compute infrastructure clusters.
Monitor and oversee cluster health, proactively identifying and resolving potential issues.
Maximize compute capacity through optimization and efficient resource allocation.
Provide 24/7 monitoring and support, leveraging automated tools and performing hands-on troubleshooting as needed.
Handle engineering escalations and collaborate with other teams to resolve complex technical challenges.
Stay up-to-date with the latest advancements in AI compute infrastructure and related technologies.

Skills And Requirements

6-8 years of relevant experience in managing and operating complex compute infrastructure, preferably in the context of machine learning or high-performance computing.
Proficient in Python and Go, with experience building operational platforms, workflow automation systems, and reliability tooling for large-scale infrastructure environments.
Experience and Expertise in distributed systems is a must.
Deep understanding of Linux-based compute systems and command-line tools.
Extensive knowledge of Docker containers and container orchestration platforms like k8s.
Proven ability to troubleshoot and resolve complex technical issues in a timely and efficient manner.
Experience with monitoring and alerting systems.
Should have a proven track record to own and drive challenges to completion.
Excellent communication and collaboration skills.
Ability to work effectively in a fast-paced environment.
Willingness to participate in a 24/7 on-call rotation.

Preferred Skills And Requirements

Operating and Managing large scale AI clusters.
Knowledge of technologies like Ethernet, RoCE, TCP/IP, etc. is desired.
Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure).

Location

SF Bay Area.
Toronto, Canada.
Bangalore, India.

Why Join Cerebras

About

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here!

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Apply About employer

More about this job

Responsibilities

Manage and operate large-scale AI compute clusters using the Wafer-Scale Engine to ensure high availability and performance. Develop software solutions for monitoring, automation, and fleet management to optimize compute capacity.

Requirements

Requires 6-8 years of experience in complex compute infrastructure with proficiency in Python, Go, and containerization technologies. Candidates must have deep expertise in Linux-based systems and distributed systems, with a willingness to participate in a 24/7 on-call rotation.

Skills

Python
Go
Docker
Kubernetes
Linux
Distributed Systems
Cluster Operations
Monitoring and Alerting
Workflow Automation
API Development
Ethernet
RoCE
TCP/IP
Cloud Computing
High Performance Computing
Troubleshooting

Visa sponsorship

Not detected in the job text

Keywords

AI Chip
Wafer-Scale Engine
WSE
Machine Learning
HPC
Docker
K8s
Python
Go
Linux
Distributed Systems
RoCE
TCP/IP
Ethernet
AWS
GCP
Azure
Cluster Operations
Infrastructure
Monitoring
Automation
API
Reliability Tooling
Inference
Training
Semiconductor
Compute Capacity
Fleet Management
On-call
Scalable O&M

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