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Added 23 mins ago
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Senior Forward Deployed Engineer
Didero
Toronto, ON
- Full-time
We are looking for a Senior Forward Deployed Engineer to join our team. This role is ideal for a technically strong, customer-facing engineer who can understand complex customer operations,…
Added 23 mins ago
L
Security Engineer, Vulnerability Management
LiveKit
Canada
- Full-time
…their data and their business at risk. We are hiring a Security Engineer to build and run our vulnerability management and security operations program. Vulnerability management is a core…
Added 1 hour ago
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Staff Site Reliability Engineer, Application
Guidewire Software
Toronto, ON
- Full-time
…team. We are the architects of stability for the Guidewire Cloud Platform, ensuring the world's leading P&C insurers can depend on our mission-critical applications. As a Staff Site…
Added 1 hour ago
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AI Inference Core - Software Integration Engineer
Cerebras
Toronto, ON
- Full-time
…inference speeds; over 10 times faster than GPU-based hyperscale cloud inference…
Added 2 hours ago
D
Forward Deployed Engineer
Didero
Toronto, ON
- $90,000 to $130,000 CAD / year
- Full-time
We are looking for a new-graduate Forward Deployed Engineer to join our team in Toronto. This role is for a technically strong, curious engineer who wants to work directly with customers,…
Added 2 hours ago
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IVR Automation Engineer
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Toronto, ON
- $35 to $40 CAD / hour
- Contract
Experience with Genesys Cloud or another CCaaS platform
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Member of Technical Staff (Migrations)
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Toronto, ON · North York, ON
- Full-time
…and Cockroach Continuum. We're looking for a staff software engineer to help build out the Migration Assistant, expand the capabilities of the MOLT toolkit, and to drive innovation around…
Added 3 hours ago
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Senior Backend Engineer (Python/GCP)
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Toronto, ON
- Contract
…focused on building next-generation applications on Google Cloud Platform (GCP). The team is developing scalable, cloud-native solutions and is seeking experienced Backend Engineers to…
Added 3 hours ago
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Founding Product & Solutions Lead
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Toronto, ON
- Full-time
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Added 4 hours ago
M
Teleop Platform Engineer, Real-Time Systems & UI
Mecka
Remote, Canada
- $200,000 to $240,000 CAD / year
- Full-time
- Remote
3+ years building production level real-time networked systems: video streaming, video conferencing, cloud gaming, remote desktop, live broadcast, or similar.
Added 4 hours ago
M
Solution Engineer - Cloud & AI Applications
Microsoft
Toronto, ON
- Full-time
…dynamic environment? If so, we invite you to join our team as a Cloud & AI Solution Engineer in AI Applications for Enterprise customers at Microsoft Canada. Here, you'll be at the…
Added 4 hours ago
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Cloud & AI Solution Engineer - Azure Platform
Microsoft
Toronto, ON
- Full-time
Are you curious, enthusiastic about infrastructure, and ready to solve complex challenges in the AI era? Join us as a Cloud & AI Solution Engineer - Azure Platform for enterprise and…
Added 4 hours ago
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Principal Software Engineer - Collateral Treasury Trading Platforms
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Toronto, ON
- Full-time
Build cloud-native applications on Google Cloud Platform (GCP) with strong understanding of deployment patterns, scalability, resilience and managed services
Added 5 hours ago
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Senior Site Reliability Engineer
Punt
Canada
- Full-time
We’re seeking a Senior Site Reliability Engineer to join Production Engineering, the team that help advance our infrastructure, security, reliability, and platform maturity. This is a…
Added 5 hours ago
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Backend Engineer (Intermediate)
Punt
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- Full-time
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Added 5 hours ago
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Senior Data Engineer (Lead)
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…new category: the most advanced and engaging social gaming platform in the…
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Site Reliability Engineer (Intermediate)
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Added 5 hours ago
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Senior Backend Software Engineer
Punt
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- Full-time
We’re seeking a Senior Backend Engineer to help design, build, and scale our next-generation social gaming platform. You’ll work on highly concurrent systems, architecting APIs and backend…
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Data Engineer (Intermediate)
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Associate Data Engineer
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Added 6 hours ago
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Associate Cloud Engineer
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Cerebras

AI Inference Core - Software Integration Engineer

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Dec 5, 2026
Posting language: English
Posted: Nov 5, 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 a Software Integration Engineer to join the AI Inference Core team at Cerebras. This team sits at the intersection of AI infrastructure, distributed systems, compilers, runtimes, kernels, and hardware/software co-design.

The Innovation Engine for Inference Core - turning ideas into reality.

You will help take ambitious ideas from concept to working reality across the Cerebras inference stack. You will integrate and validate cross-component projects of high complexity, often on accelerated timelines, and work directly with engineers across AI, runtime, compiler, kernel, systems, and hardware teams.

A Special Task Force, Not a Typical Engineering Role

Zero-to-one mission: Take incomplete ideas and early prototypes all the way to working, validated capabilities.
Cross-stack complexity: Move across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware - not just one component or codebase.
Accelerated and dynamic cadence: Expect focused daily syncs, rapidly changing priorities, and periods of intense integration work. This is not a role for engineers seeking strictly regular, predictable work hours.
Comfortable on the hot seat: Take ownership when the path is unclear, make sound decisions with incomplete information, and stay effective when timelines are tight.
Bias for action: At critical moments, the mindset is “No Process, No Documentation, Just Get Stuff Done!!!” Cut through unnecessary ceremony, deliver the result, and then turn what you learned into better automation, diagnostics, documentation, and repeatable practices.
Team multiplier: Always push the work forward while raising the pace, clarity, and effectiveness of the people around you. We want people who bring the team with them - not lone heroes.

We prefer candidates with experience in software/hardware co-design or other complex systems, but that experience is not required. We welcome exceptional junior engineers who are eager to learn, do not shy away from ambiguity or hard work, and can demonstrate strong fundamentals, curiosity, ownership, and persistence.

What You Will Do

Turn new inference ideas and features into integrated, working capabilities across the Cerebras platform.
Take high-value projects from zero to one - from an incomplete idea or prototype to a working, validated capability.
Integrate and validate software components spanning AI frameworks, runtime, compiler, kernels, distributed systems, and hardware.
Drive cross-component projects of high complexity from problem definition through integration, validation, and release readiness.
Collaborate closely with software and hardware engineers to make co-design trade-offs and resolve system-level issues.
Investigate and debug difficult failures across large-scale AI workloads, distributed software, infrastructure, and hardware boundaries.
Work effectively on accelerated timelines while keeping technical risks, dependencies, and decisions visible.
Participate in focused daily syncs, manage rapidly changing priorities, and drive ambiguous situations toward concrete outcomes.
Identify bottlenecks, failure modes, edge cases, and integration gaps that affect inference correctness, performance, or delivery.
Capture the essential lessons from urgent work so the next integration is faster and less chaotic.
Create momentum beyond your own work by helping teammates move faster, make better decisions, and close difficult problems together.

Minimum Skills & Qualifications

Strong software-engineering fundamentals and programming ability in Python, C++, Go, or a similar language.
Experience with software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems.
Experience debugging complex systems, distributed software environments, or large-scale compute clusters.
Experience with AI infrastructure, model deployment, LLMs, or multimodal workloads.
Exposure to performance debugging, profiling, observability, or failure analysis.
Familiarity with microservices, containers, cluster orchestration, cloud infrastructure, or high-performance computing.
Experience - through professional work, internships, research, academic projects, open source, or equivalent hands-on work - building or debugging software systems.
Clear communication and strong collaboration across disciplines and levels of experience.

Preferred Skills

Experience in a startup or similarly fast-moving, resource-constrained engineering environment.
Demonstrated experience taking a project from zero to one: turning an ambiguous problem, early idea, or prototype into a working and reliable capability.
Demonstrated ability to break down ambiguous technical problems, form hypotheses, gather evidence, and drive issues to resolution.
Curiosity about how complex systems behave across component boundaries.
Willingness to read unfamiliar code, learn new layers of the stack, and take ownership beyond a narrowly defined area.
Ability to work hard and stay effective during periods of uncertainty, rapid change, and accelerated delivery.
Track record of driving cross-team projects from an incomplete idea to a reliable working result.

Location

This role follows a hybrid schedule and requires in-office presence 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.

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More about this job

Responsibilities

Integrate and validate inference capabilities across AI frameworks, runtimes, compilers, kernels, distributed systems, infrastructure, and hardware, taking projects from early ideas or prototypes through release readiness. Debug complex system-level issues, coordinate across software and hardware teams, and improve integration practices while delivering on accelerated timelines.

Requirements

Candidates need strong software engineering fundamentals and hands-on experience building or debugging software systems, with relevant exposure to areas such as AI infrastructure, hardware accelerators, compilers, runtimes, distributed systems, or large-scale compute. The role also calls for clear cross-disciplinary communication, collaboration, and the ability to take ownership and resolve ambiguous technical problems.

Skills

Python
C++
Go
Software Integration
Software/Hardware Co-Design
AI Infrastructure
Distributed Systems
Compilers
Kernels
Runtimes
Hardware Accelerators
Debugging
Performance Profiling
Model Deployment
Cluster Orchestration
High-Performance Computing

Visa sponsorship

Not detected in the job text

Keywords

Cerebras Systems
AI Inference
AI Infrastructure
Software Integration
Software/Hardware Co-Design
Distributed Systems
AI Frameworks
Compilers
Kernels
Runtimes
Hardware Accelerators
Python
C++
Go
Large Language Models
Multimodal Workloads
Model Deployment
Performance Debugging
Profiling
Observability
Failure Analysis
Microservices
Containers
Cluster Orchestration
Cloud Infrastructure
High-Performance Computing
Inference Correctness
System Integration
Release Readiness
Cross-Team Collaboration

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