Find work in Canada.

537,575 jobs across our Canadian network. How we count

Jobs in Canada

Email me new jobs Save this search

Added 10 days ago
BS
Artificial Intelligence Specialist
Bay Street Staffing
Toronto, ON · Greater Toronto Area, Canada
- Full-time
A degree or diploma in computer science, engineering, business technology or a related field
Added 10 days ago
KR
Quality Assurance Engineer + IoT
KTek Resourcing
Canada
- Full-time
Able to provide requirements of the testing data needed to execute the test plan
Added 10 days ago
K
Lead Data Engineer
Kabam
Vancouver, BC
- Full-time
The Lead Data Engineer owns Kabam's central data platform end to end, from the game telemetry standard through to the certified data layer that analytics, finance, data science and AI tools…
Added 10 days ago
R
Principal AI Engineer, AI DLC Platform
RBC
Toronto, ON
- Full-time
Software engineering depth: proficiency in Python, Java or C++ with strong engineering fundamentals.
Added 10 days ago
SL
Principal AI Engineer
Sun Life
Toronto, ON · Waterloo, ON · Sun Life Waterloo King
- Full-time
Canada IT – Platforms and Engineering Domain is looking for a Principal AI Engineer with at least 10 years of engineering experience. This role will be instrumental in driving innovation,…
Added 10 days ago
C
Robotics & Software Engineer
Correct-AI
AB · Greater Edmonton Metropolitan Area
- Full-time
Collaborate with engineering teams to analyze field data, resolve issues, and improve system reliability and performance.
Added 10 days ago
TC
Observability Engineer
TechNeptune Consulting Inc.
Montreal, QC · Greater Montreal Metropolitan Area
- $65 to $75 CAD / hour
- Contract
Enable teams to leverage observability data for reliability, performance, and security use cases; provide actionable recommendations.
Added 10 days ago
C
Director of AI Applications Development
CIBC
Toronto, ON
- Full-time
Technical leadership - Guide architecture and engineering decisions for enterprise AI applications, with a focus on security, scalability, performance, and reliability. Support the…
Added 10 days ago
R
Spécialiste en automatisation manufacturière / Manufacturing Automation Specialist
RTX
Longueuil, QC
- Full-time
Maîtrise des langages de programmation (C#, Java, Python);
Added 10 days ago
E
Agentic AI Developer
Equifax
Toronto, ON · CAN - Ontario - Toronto
- Full-time
Software Engineering Mastery: Strong proficiency in Python or TypeScript, with a deep understanding of asynchronous programming, API design, and microservices architecture.
Added 10 days ago
Rust Developer
Charger Logistics Inc
Brampton, ON
We’re looking for a hands-on Rust Developer to build fast, reliable, memory-safe backend systems. You’ll design and write production Rust services, improve performance, and work closely…
Added 10 days ago
S
Intern, Engineering Services (8 Months)
Seaspan
North Vancouver, BC
- Full-time
The Intern, Engineering Services will be responsible for assisting the Engineering Services team in the successful completion of an Integrated Cadmatic eShare to Aras PLM integration. This…
Added 10 days ago
C
Staff Backend Engineer | Remote, US & Canada
Cube
Canada
- Full-time
Engineering Leader: Proven ability to define engineering standards, design reusable abstractions, and improve developer velocity through internal tooling and frameworks.
Added 10 days ago
MT
Physical Design Engineer
Mirafra Technologies
Canada
- Full-time
…optimizing, and automating physical design workflows using Tcl and Python, incorporating AI-assisted development tools like GitHub Copilot to accelerate script delivery and engineering…
Added 10 days ago
PC
Technical Architect
Pyramid Consulting, Inc
Toronto, ON
- Contract
Top Skills: Python, Node Js, Mongo DB, Microservices
Added 10 days ago
RC
Senior QA Engineer
Rexall Care Network
Mississauga, ON
- Full-time
Develop and execute automated API and service-level tests to validate system contracts, integration points, and data flows across Rexall’s digital ecosystem.
Added 10 days ago
Data Engineer – Informatica IDMC & ETL Development
Capco
Toronto, ON
Experience with Python, scripting or automation to support data engineering and pipeline orchestration.
Added 10 days ago
IF
Senior Analyst, Quantitative Data Science
iA Financial Group
Montreal, QC · Quebec, QC
- Full-time
The Senior Analyst, Quantitative Data science, plays a central role in developing and scaling analytical data products used across Investments. This role combines financial domain…
Added 10 days ago
SI
Full-Stack Developer (Rust & WebAssembly)
SuperQubit Inc.
Markham, ON
- $80,000 to $120,000 CAD / year
- Full-time
We are looking for a Full-Stack Developer (Rust & WebAssembly) to join our engineering team and contribute to the development of modern, secure, scalable software applications and platforms.
Added 10 days ago
E
Quality Engineer - Banking Mobile (iOS/Android) & Automation Testing
Experis
Toronto, ON
- Contract
Solid understanding of at least one programming language (e.g., JavaScript/TypeScript, Python, Java, or C#).
Added 10 days ago
UI
Process and automation specialist
UAP Inc.
Longueuil, QC
- Full-time
Develop automated solutions (Python, VBA, SQL, Power Platform, or other relevant tools) to optimize processes related to pricing, products, and master data.
Added 10 days ago
C
AI Inference Core - Senior SDET, Release Integration Testing
Cerebras
Toronto, ON
- Full-time
This is a highly technical, hands-on engineering role requiring strong software development, automation, and debugging skills. You will independently own complex testing initiatives,…
Added 10 days ago
F
Senior Manager, Credit Modeling and Strategy
Flexiti
Toronto, ON · North York, ON
- Full-time
Have solid proficiency in data analysis tools (SAS, Python, R, SQL, DataBricks)
Added 10 days ago
JG
Senior Python Developer with PySpark and AWS
J&M Group
Toronto, ON
- Full-time
React, JupyterLab, Data Engineering/Data Science
Added 10 days ago
C
AI Inference Core - Technical Lead Manager, Release Qual & Integration
Cerebras
Toronto, ON
- Full-time
Strong software-engineering fundamentals and programming ability in Python Go, or a similar language.

Cerebras

AI Inference Core - Senior SDET, Release Integration Testing

Toronto, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Nov 18, 2026
Posting language: English
Posted: Oct 19, 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 experienced, hands-on Senior Software Development Engineer in Test (SDET) to join the Release Integration Testing (RIT) function within Release & Feature Qualification for AI Inference Core.

The Production Engine for Inference Core - turning integrated features into reliable production releases.

In this role, you will develop sophisticated test automation, validate complex AI inference systems, investigate cross-stack failures, and drive improvements in release quality and reliability. You will work across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware to identify integration risks and ensure production readiness.

This is a highly technical, hands-on engineering role requiring strong software development, automation, and debugging skills. You will independently own complex testing initiatives, contribute to test architecture and release qualification strategies, and collaborate closely with engineering teams to improve system reliability.

Release Integration Testing (RIT) is the bridge between feature qualification and release qualification. Feature teams retain ownership of feature design, feature-level qualification, and feature regression. RIT focuses on integration readiness, cross-stack validation, regression stability, and first-pass rollout triage for AI Inference Core.

What Makes This Role Distinct

Software engineering applied to quality: Design and develop scalable test automation, frameworks, diagnostics, and tooling to validate complex AI inference systems - not just execute test cases.
Cross-stack technical challenges: Debug and validate interactions across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware.
Integration and release ownership: Independently drive integration testing, regression validation, and release qualification activities for complex inference-core features.
Inference-path validation: Identify and test high-risk interactions across runtime, host, device programming, memory, scheduling, and model execution.
Production reliability: Improve master and release-branch stability through robust automation, failure analysis, and actionable quality metrics.
Technical collaboration: Partner with SDETs, software engineers, infrastructure teams, and release owners to resolve complex issues and improve engineering efficiency.

What You Will Do

Design, develop, and maintain automated test frameworks, tools, and infrastructure to validate AI inference software across multiple components and system layers.
Independently own integration testing and qualification activities for complex inference-core features, identifying dependencies, interaction risks, and potential coverage gaps.
Develop and execute comprehensive end-to-end, integration, regression, and system-level tests across AI frameworks, runtime, compiler, kernels, infrastructure, and hardware.
Analyze unit, simulation, benchmark, feature-test, and integration results to assess readiness, identify gaps, and provide evidence-based recommendations for release qualification.
Investigate and debug complex cross-stack failures, perform root cause analysis, collaborate with engineering teams on fixes, and implement automated tests to prevent regressions.
Improve master and release-branch stability by identifying regressions, triaging failures, validating fixes, and contributing to release-quality metrics and reporting.
Build and enhance internal tooling for test automation, diagnostics, monitoring, dashboards, CI/CD workflows, and release qualification pipelines.
Collaborate with feature engineering, Integration, Core Infrastructure, and release teams to improve test coverage, accelerate debugging, and support coordinated feature rollouts.
Contribute to test architecture, risk-based testing strategies, and continuous improvements in automation efficiency, system observability, and release reliability.
Provide technical guidance and mentorship to junior engineers through code reviews, debugging sessions, and sharing testing best practices.

Minimum Skills & Qualifications

Strong software engineering fundamentals with professional experience developing software, automated testing frameworks, or test infrastructure.
Proficiency in Python, Go, or a similar programming language, with demonstrated experience writing maintainable, production-quality code.
Experience designing, developing, and maintaining automated tests and frameworks for complex software systems.
Strong debugging and problem-solving skills, including the ability to investigate failures across multiple components, analyze logs and system behavior, and identify root causes.
Solid understanding of software testing methodologies, including integration testing, system testing, regression testing, and end-to-end validation.
Experience working with CI/CD pipelines, test automation infrastructure, and software development workflows.
Working knowledge of operating systems, networking, distributed systems, or systems-level software concepts.
Ability to independently own complex technical problems, prioritize testing efforts, and drive issues through resolution.
Strong communication and collaboration skills, with experience working across multiple engineering teams to deliver reliable software.

Preferred Skills

Experience testing or developing distributed systems, infrastructure software, runtime systems, compilers, kernels, or other low-level software.
Experience with AI/ML infrastructure, LLM inference, model deployment, multimodal workloads, or large-scale compute environments.
Exposure to hardware accelerators, GPU systems, software/hardware integration, or high-performance computing.
Experience building scalable test frameworks, distributed test systems, release pipelines, or internal developer tools.
Familiarity with performance testing, profiling, observability, fault injection, reliability engineering, or production failure analysis.
Experience with containers, Kubernetes, cloud infrastructure, cluster orchestration, or large-scale distributed computing environments.
Experience using debugging and observability tools to diagnose complex system-level issues.
Experience working in fast-paced engineering environments, including startups or teams developing complex systems software.

What Success Looks Like

You independently deliver robust, scalable automation and test infrastructure that improves integration and release qualification.
Complex cross-stack defects are identified and resolved earlier in the development cycle, reducing issues discovered during final release qualification or production.
Regression testing provides reliable, actionable signals that improve master and release-branch stability.
Debugging cycles are shorter through improved diagnostics, automation, and effective collaboration across engineering teams.
Test coverage and qualification processes evolve to support increasingly complex AI inference features and workloads.
Your technical contributions improve release predictability, engineering efficiency, and overall system reliability.
You are a trusted technical contributor who helps raise engineering quality through strong code, sound judgment, and mentorship.

Location

This role follows a hybrid schedule and requires in-office presence at least three days per week. Fully remote work is not available.
Office locations: Sunnyvale, CA or Toronto, ON.

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

Develop and maintain automated test frameworks and infrastructure, and independently lead integration, regression, and release qualification testing for AI inference systems across software and hardware layers. Investigate cross-stack failures, improve release stability and diagnostics, collaborate with engineering teams, and mentor junior engineers.

Requirements

Candidates need strong software engineering and automation experience, proficiency in Python, Go, or a similar language, and expertise in testing, debugging, and CI/CD workflows. They should understand systems concepts and be able to independently drive complex technical issues to resolution while collaborating across engineering teams.

Skills

Python
Go
Test Automation
Integration Testing
System Testing
Regression Testing
End-to-End Testing
CI/CD
Debugging
Root Cause Analysis
Distributed Systems
AI/ML Infrastructure
LLM Inference
Release Qualification
Performance Testing
Kubernetes

Visa sponsorship

Not detected in the job text

Keywords

AI Inference
Release Integration Testing
Test Automation
Python
Go
AI Frameworks
Runtime Systems
Compilers
Kernels
Distributed Systems
CI/CD
Regression Testing
System Testing
End-to-End Testing
Release Qualification
Root Cause Analysis
Diagnostics
Monitoring
Dashboards
LLM Inference
Model Deployment
Hardware Accelerators
High-Performance Computing
Performance Testing
Observability
Fault Injection
Kubernetes
Cloud Infrastructure
Cluster Orchestration

Report this job