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Added 1 month ago
BC
Support Engineer III
Blackpoint Cyber
Remote, Canada
- $81,600 to $102,000 CAD / year
- Full-time
- Remote
Collaborate with the Engineering and Product teams to identify, report, and prioritize software bugs and enhancements.
Added 1 month ago
P
Data Integration Engineer
Prophix
Toronto, ON · Etobicoke, ON
- Full-time
A Prophix Data Integration Engineer enables seamless, automated connections between client data sources and the Prophix platform. Working on the Professional Services team and with…
Added 1 month ago
AI
Forward Deployed AI Engineer
AGF Investments
Toronto, ON
- Full-time
Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, Information Technology, or a related discipline.
Added 1 month ago
AI
AI Platform Engineering Lead
AGF Investments
Toronto, ON
- Full-time
The AI Platform Engineering Lead is the senior technical authority for how AI is built at AGF. Reporting to the VP, Technology Services, the role defines the blueprints that AI solutions…
Added 1 month ago
M
Sr. Data Platform Engineer
McKesson
Mississauga, ON
- Full-time
The Data Engineering – Level 4 provides technical leadership in designing, implementing, and optimizing McKesson’s enterprise data infrastructure to enable advanced analytics and…
Added 1 month ago
2027 Intern Program, Technology Innovation - Future Opportunities
Bell
Montreal, QC
Bachelor's degree, master’s degree, or college diploma in a technology-related field (e.g., Computer Science, Software Engineering, AI, Data Science, Information Technology, or a related…
Added 1 month ago
SC
Senior Groundwater Modeler
SLR Consulting
AB · Guelph, ON · Toronto, ON · Saskatoon, SK · Victoria, BC · Nanaimo, BC · Vancouver, BC · Calgary, AB
- Full-time
We are SLR Consulting (Canada), an 1000+ team of advisory, environmental, engineering, and regulatory professionals across Canada. We deliver services through the integration of over 30…
Added 1 month ago
GD
Copy of Software Engineering Developer, DevOps
General Dynamics Missions System International
Calgary, AB · Ottawa, Ontario
- $85,000 to $110,000 CAD / year
- Full-time
At General Dynamics Mission Systems–Canada, we’re not just engineering technology - we’re shaping the future of defence and security. Our teams design and deliver advanced, mission-critical…
Added 1 month ago
P
Senior Manager, AdTech Engineering
Pelmorex
Oakville, ON
- Full-time
…architecture, and organizational execution for our flagship data and advertising technology platforms. Bridging front-end SaaS applications with large-scale data engineering infrastructure,…
Added 1 month ago
Senior Service Reliability Engineer
Fitch Group
Toronto, ON
…Fitch Group delivers vital credit and risk insights, robust data, and dynamic tools to champion more efficient, transparent financial markets. With over 100 years of experience and…
Added 1 month ago
Q
Business and Data Analyst
Qfin
Toronto, ON · North York, ON
- Full-time
Bachelor's degree or above in Mathematics, Statistics, Economics, Finance, Computer Science, Engineering, Data Science or another quantitative discipline.
Added 1 month ago
P
Senior Manager, AdTech Engineering
Pelmorex
Oakville, ON
- Full-time
…architecture, and organizational execution for our flagship data and advertising technology platforms. Bridging front-end SaaS applications with large-scale data engineering infrastructure,…
Added 1 month ago
R
Engineering Manager, Data
Robinhood
Toronto, ON
- Full-time
Our Core Data Engineering team is responsible for designing and building all foundational datasets used across Robinhood and within our operational business areas. We build the foundational…
Added 1 month ago
B
Precision Technology Summer Associate
BASF
Saskatoon, SK
- Temporary
Utilizing your comfort with statistical programming in R or Python to take on data analysis and model development tasks that enhance your problem-solving skills.
Added 1 month ago
C
Staff Generative AI Engineer - Vice President
Citi
Mississauga, ON
- Full-time
Expert-level proficiency in Python is a must-have, with a deep understanding of its ecosystem for AI/ML development, data engineering, and backend services. Full-stack development…
Added 1 month ago
B
Principal AI Cloud Engineer
BMO
Toronto, ON · FCP
- Full-time
The Team - We accelerate BMO’s AI journey by building cloud-native AI solutions. Our team combines engineering excellence with cutting-edge AI to deliver scalable, secure, and responsible…
Added 1 month ago
L
Murex DevOps
Luxoft
Toronto, ON
- Full-time
Ensure compliance with security and data governance requirements
Added 1 month ago
M
Applied AI Scientist
Mphasis
Canada
- Full-time
This is not primarily a conventional data science role, an LLM application-development role, or a prompt-engineering role. We are interested in people who want to understand how intelligent…
Added 1 month ago
NM
System Hardware Engineering Tester
Natus Medical Incorporated
Oakville, ON
- Full-time
System Hardware Engineering Tester – Natus Neuro
Added 1 month ago
C
Staff Data Engineer
commonsku
Remote, Canada
- $160,000 to $180,000 CAD / year
- Full-time
- Remote
Our core foundation for the Data Team is built on Snowflake. The rest of our tech stack is built on PHP, Python, React, mySQL and our infrastructure is in AWS.
Added 1 month ago
C
Staff Software Engineer - Tools & Infrastructure / DevOps
Cerebras
Toronto, ON
- Full-time
Design and drive improvements to internal build infrastructure, test infrastructure, developer tooling, and automation that increase developer velocity and engineering productivity.
Added 1 month ago
C
ML Systems Integration Engineer
Cerebras
Toronto, ON
- Full-time
Continuously improve internal engineering workflows related to debugging, testing, and automation.
Added 1 month ago
C
Full Stack LLM Engineer
Cerebras
Toronto, ON
- Full-time
Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field.
Added 1 month ago
C
Senior SDET, Inference Platform
Cerebras
Toronto, ON
- Full-time
Partner with engineering teams to ensure high-quality, production-ready releases of the Cerebras Inference Platform.
Added 1 month ago
C
Staff Cloud Infrastructure Engineer
Cerebras
Toronto, ON
- Full-time
Drive the design and architecture of secure, scalable cloud infrastructure and identity platforms in AWS and our own data centers.

Cerebras

Senior SDET, Inference Platform

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Experience: 3+ years of experience in software engineering, QA/quality engineering, systems engineering, or infrastructure development.
Posting language: English
Posted: Sep 23, 2026

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.

About The Role

We are looking for an Inference Platform SDET to join the Inference Service Quality team at Cerebras and work on the inference platform. This team sits at the intersection of distributed systems, cloud and cluster infrastructure, and the software stack that serves the world's fastest AI inference.

In this role, you will own the quality and reliability of the infrastructure that deploys and runs the Cerebras Inference Platform - from CI/CD pipelines and Kubernetes-based deployments to ingress, load balancing, and service discovery. You will validate the platform both in cloud environments and on real Cerebras clusters, working side by side with the Inference Platform development team to catch issues before our customers do.

This is an excellent opportunity for engineers who enjoy infrastructure, automation, and debugging across the full deployment stack, and who want to ensure that a platform serving inference at massive scale stays fast, reliable, and production-ready.

Responsibilities

Design, build, and maintain test infrastructure and automation for deploying and validating the Cerebras Inference Platform.
Validate the platform across environments - from cloud-managed Kubernetes to deployments running on Cerebras hardware.
Test and verify deployment infrastructure including Kubernetes workloads, CI/CD pipelines, ingress and service discovery, NGINX, and load balancing.
Collaborate closely with the Inference Platform development team to ensure new features and platform capabilities ship reliably.
Investigate and debug complex issues spanning networking, orchestration, deployment, and distributed services.
Develop and maintain testbeds used to validate platform performance, scalability, and reliability.
Identify failure points, bottlenecks, and edge cases that impact platform stability and inference performance.
Contribute to test plans and validation strategies for new platform features and releases.
Improve observability, diagnostics, and debugging workflows across the inference platform stack.
Partner with engineering teams to ensure high-quality, production-ready releases of the Cerebras Inference Platform.

Minimum Skills & Qualifications

3+ years of experience in software engineering, QA/quality engineering, systems engineering, or infrastructure development.
Strong programming skills in Python and/or Go (experience with both is a plus).
Experience building automation tools, testing frameworks, or internal developer tooling.
Hands-on experience with CI/CD systems (e.g., Jenkins)
Experience debugging complex systems, distributed services, or networked infrastructure.
Familiarity with systems-level development, infrastructure tooling, or platform integration.
Strong problem-solving skills and the ability to investigate issues across multiple system and infrastructure layers.
Excellent communication and collaboration skills.
Experience mentoring junior engineers

Preferred Skills

Hands-on experience with Kubernetes and container orchestration in a real production or staging environment.
Experience with cloud-managed Kubernetes such as Amazon EKS.
Experience with GitOps/deployment tooling (e.g., ArgoCD).
Familiarity with ingress controllers, service discovery, NGINX, and load balancing.
Experience with build systems such as Bazel.
Experience with cluster tooling and operations (e.g., k9s).
Exposure to performance debugging, profiling, or system observability tools.
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads

Location: Toronto / Sunnyvale

Team: Inference Service Quality

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.

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More about this job

Responsibilities

Build and maintain automated test infrastructure to validate the Inference Platform across cloud-managed Kubernetes environments and Cerebras hardware, including deployments, CI/CD, networking, ingress, and load balancing. Investigate cross-stack issues, maintain testbeds for performance and reliability validation, improve observability and debugging, and collaborate with development teams to deliver production-ready releases.

Requirements

Candidates need at least three years of experience in software engineering, quality engineering, systems engineering, or infrastructure development, along with strong Python and/or Go skills and experience building automation or testing tools. They should be able to debug distributed systems and networked infrastructure, work with CI/CD systems, and communicate and collaborate effectively; Kubernetes, EKS, GitOps, and inference infrastructure experience are preferred.

Skills

Python
Go
Test Automation
Testing Frameworks
CI/CD
Kubernetes
Amazon EKS
ArgoCD
NGINX
Ingress Controllers
Service Discovery
Load Balancing
Distributed Systems Debugging
Bazel
Cluster Operations
Performance Debugging

Visa sponsorship

Not detected in the job text

Keywords

Inference Platform
Test Infrastructure
Test Automation
Python
Go
CI/CD
Jenkins
Kubernetes
Amazon EKS
ArgoCD
GitOps
NGINX
Ingress Controllers
Service Discovery
Load Balancing
Distributed Systems
Cloud Infrastructure
Cluster Infrastructure
Cerebras Hardware
Bazel
k9s
Performance Testing
Scalability
Reliability
Observability
Model Serving
ML Inference
GPU-Accelerated Workloads
Networking

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