Jobs in Canada

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Added 1 month ago
SR
Senior Robotics Engineer
Strive Robotics
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Senior engineers with evidence of shipped robotic or cyber-physical systems, strong Python/C++ foundations, and clear technical judgment across learning, programming, sensing, and mechanics.
Added 1 month ago
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Machine Learning Engineer Intern
Workday
Toronto, ON · Vancouver, BC · Canada, BC, Vancouver
- Full-time
We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and…
Added 1 month ago
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Software Development Engineer Intern
Workday
Vancouver, BC · Canada, BC, Vancouver
- Full-time
As a Software Development Engineer Intern, you will jump right into building real-world solutions and experience what it's like to be a developer at Workday. You'll work closely with a team…
Added 1 month ago
Senior Software Engineer - Agentic AI security - 2 positions
Tigera
Vancouver, BC
…generation of agentic AI workloads running on Kubernetes and beyond. With Lynx by Tigera, we have a platform that discovers agentic AI on any host, secures it through the kernel and our…
Added 1 month ago
KG
DevOps Platform Engineer | AI & LLMOps Infrastructure
K&K Global Talent Solutions INC.
ON · Ontario, Canada
- Full-time
Position: DevOps Platform Engineer | AI & LLMOps Infrastructure
Added 1 month ago
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Senior Mechanical Engineer (Semiconductor Packaging)
Inpho
Ottawa, ON · Kanata, ON
- Full-time
We are looking for a Senior Mechanical Engineer who thrives at the intersection of precision design and robust process development to help us bring our optical subassemblies to the global…
Added 1 month ago
JG
FORWARD DEPLOYEMENT ENGINEER
J&M Group
Canada
- Full-time
Must Have Technical/Functional Skills
Added 1 month ago
Senior Backend Engineer II - Patient Experience
Prenuvo
Vancouver, BC
Our in-house Python communications service converts event bus domain events into patient messaging via Iterable, AWS SES, SMS, and push. Key challenges involve ensuring reliable,…
Added 1 month ago
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Associate Software Engineer
CARFAX
London, ON
- $64,000 to $96,000 CAD / year
- Full-time
This position will require 2 days per week in our London,ON office subject to change with future business needs
Added 1 month ago
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Software Engineer, GPU Inference
Cerebras
Toronto, ON
- Full-time
Strong programming ability in C++ and Python, including experience with multithreading, concurrency, memory management, and performance-sensitive software.
Added 1 month ago
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GenAI Prompt Engineer
Yochana
Toronto, ON
- Contract
AI Response Validation: Analyze and validate AI-generated outputs to ensure they meet quality standards, are contextually appropriate, and align with user needs.
Added 1 month ago
Test Development Team Lead
Nureva
Calgary, AB
The ideal candidate is a strong software engineer with a passion for quality, automation, and
Added 1 month ago
OT
Network Engineer III
Opti9 Technologies
Remote, Canada
- $115,000 to $145,000 CAD / year
- Full-time
- Remote
Is this you? Are you a Network Engineer III with experience working in cloud service provider environment that strives for customer excellence, revels in being a part of constant…
Added 1 month ago
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Software Engineer
CARFAX
London, ON
- $78,000 to $116,000 CAD / year
- Full-time
This position will require 2 days per week in our London,ON office subject to change with future business needs
Added 1 month ago
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Senior Software Engineer
CARFAX
London, ON
- $93,000 to $139,000 CAD / year
- Full-time
This position will require 2 days per week in our London,ON office subject to change with future business needs
Added 1 month ago
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Staff Software Engineer - Open Source Data Platform (ODP)
Acceldata
Kitchener, ON
- Full-time
We are seeking a Staff Engineer with at least 9 years of experience in distributed systems or data platform development. In this role, you will be a technical leader responsible for…
Added 1 month ago
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Artificial Intelligence Consultant
SMARTFOX
Canada
- Full-time
Build proofs of concept and production pilots with Python and platforms such as Azure OpenAI, AWS Bedrock, Google Vertex AI, OpenAI, Anthropic, or Hugging Face
Added 1 month ago
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Artificial Intelligence Engineer
Flexstaf I.T. Inc.
Canada
- Contract
…AI application development and solution architecture (70%) with client consulting, training, and enablement…
Added 1 month ago
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Adobe Site Reliability Engineer (SRE) – CDN & Web Performance
I8IS - Infiniti Software Solutions
Toronto, ON
- Full-time
We are seeking a highly skilled and proactive Adobe Site Reliability Engineer (SRE) specializing in CDN and Web Performance to join our client's dynamic team.
Added 1 month ago
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Software Engineer in Test
LTM
Mississauga, ON
- $103,554 to $115,200 CAD / year
- Full-time
Job Role – Software Development Engineer in Test
Added 1 month ago
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GenAI Prompt Engineer
TechDoQuest
Toronto, ON
- Contract
-AI Response Validation: Analyze and validate AI-generated outputs to ensure they meet quality standards, are contextually appropriate, and align with user needs.
Added 1 month ago
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Senior Software Engineer
Pebl
Remote, Canada
- $122,835 to $180,000 CAD / year
- Full-time
- Remote
Our values guide how we operate, execute, and collaborate across borders
Added 1 month ago
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Senior Manager, Data Engineer, Applied AI Data Ingestion & Integration
BMO
Toronto, ON · FCP
- Full-time
…and AI solutions. Our team combines engineering excellence with cutting-edge AI to deliver scalable, secure, and responsible solutions that power business innovation across the bank. We are…
Added 1 month ago
AI
Senior Site Reliability Engineer - AEM - Content Delivery Network
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Toronto, ON
- Full-time
…repository is production: reconcile a merge-to-main deployment model with change control, so that every production change carries an approved record with stalling…
Added 1 month ago
KG
Senior Platform Engineer
Kinross Gold Corporation
Toronto, ON
- Full-time
…are seeking a highly technical and hands-on Senior Platform Engineer to drive the evolution of our hybrid infrastructure ecosystem spanning on-premises datacenters, cloud platforms,…

Cerebras

Software Engineer, GPU Inference

Toronto, ON, Canada

Full-time

Apply on LinkedIn About employer

Applications open in a new tab.

Job details

Job type: Full-time
Experience: 5+ years of software engineering experience, including substantial individual-contributor ownership of complex production systems.
Posting language: English
Posted: Oct 9, 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

Cerebras is building a new generation of disaggregated AI inference systems that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine.

We are hiring a Software Engineer to productionize and optimize our GPU serving stack, working across our custom inference APIs, the vLLM serving runtime, the AMD ROCm software stack, and rack-scale AMD GPU infrastructure, to make this new serving path reliable, numerically correct, observable, and exceptionally performant.

You will write production code, establish operational practices for a new accelerator fleet, and drive improvements in time to first token, throughput, tail latency, and capacity efficiency. This is a hands-on role requiring deep debugging and optimization across application, runtime, distributed systems, and hardware layers.

Responsibilities

Productionize the GPU inference stack. Design, build, deploy, and maintain the complete GPU prefill path, spanning API services, model-serving workers, vLLM, PyTorch, ROCm, GPU nodes, networking, and rack-scale infrastructure.
Own GPU operational readiness. Establish deployment, upgrade, rollback, health-checking, capacity-management, and failure-recovery practices for the AMD GPU fleet. Build automation that makes driver, firmware, runtime, model, and container compatibility explicit and reproducible.
Drive reliability in production. Define service-level indicators and objectives for GPU-backed inference. Improve fault isolation, graceful degradation, automated recovery, incident response, and post-incident remediation across the serving stack.
Improve inference performance. Profile and optimize time to first token, request throughput, tokens per second per GPU, tail latency, GPU utilization, memory efficiency, and rack-level capacity under representative production workloads.
Optimize model-serving behavior. Tune and improve scheduling, continuous batching, prefix caching, KV-cache management, tensor and expert parallelism, request admission, quantization, graph execution, and distributed communication.
Debug across system layers. Diagnose complex failures and performance regressions across application code, vLLM, PyTorch, ROCm/HIP, collective communication libraries, kernels, drivers, firmware, networking, and hardware.
Ensure numerical correctness. Build validation and regression infrastructure for model quality, numerical accuracy, precision changes, quantization, determinism, and compatibility across software and hardware releases.
Build performance and correctness infrastructure. Develop representative benchmarks, workload replay tools, profiling automation, release qualification, dashboards, and regression gates. Turn one-off investigations into repeatable engineering systems.

Minimum Qualifications

5+ years of software engineering experience, including substantial individual-contributor ownership of complex production systems.
Experience building, operating, or optimizing production inference systems for large language models, multimodal models, or similarly demanding GPU workloads.
Strong programming ability in C++ and Python, including experience with multithreading, concurrency, memory management, and performance-sensitive software.
Hands-on experience with a high-performance model-serving framework such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or an equivalent internally developed system.
Strong understanding of GPU execution and performance, including asynchronous execution, memory movement, synchronization, kernel launches, communication overhead, and profiling methodology.
Experience debugging distributed systems across multiple layers rather than treating the serving framework or accelerator runtime as a black box.
Experience with Linux, containers, Kubernetes or comparable orchestration systems, observability, CI/CD, and operating latency-sensitive services in production.
Ability to design rigorous benchmarks, interpret noisy performance results, identify bottlenecks, and translate findings into production improvements.
Strong communication and technical leadership skills, with a demonstrated ability to drive ambiguous cross-functional projects to completion.
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or equivalent practical experience.

Preferred Qualifications

Experience with AMD Instinct accelerators and the ROCm ecosystem, including HIP, RCCL, rocprofiler, AMD SMI, AITER, hipBLASLt, Composable Kernel, or related libraries and tools.
Deep CUDA experience that demonstrates an ability to transfer GPU systems knowledge across accelerator platforms.
Experience modifying or contributing to vLLM, SGLang, PyTorch, Triton, TensorRT-LLM, or another open-source ML systems project.
Experience optimizing prefill-heavy or disaggregated prefill/decode inference architectures.
Understanding of KV-cache transfer, prefix caching, continuous batching, chunked prefill, request scheduling, and memory-aware admission control.
Experience with multi-GPU and multi-node inference, including tensor parallelism, pipeline parallelism, expert parallelism, RDMA, collective communication, and failure handling.
Experience optimizing Mixture-of-Experts or multimodal models.
Knowledge of GPU kernel optimization, operator fusion, graph capture, attention kernels, GEMM tuning, and communication/computation overlap.
Experience with reduced-precision inference and quantization formats such as BF16, FP8, FP4, INT8, or INT4, including validation of their numerical and model-quality effects.
Experience building numerical-comparison, determinism, model-validation, or performance-regression test systems.
Experience collaborating directly with accelerator vendors, framework maintainers, or open-source communities.

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

Productionize and operate the GPU prefill serving stack across APIs, vLLM, PyTorch, ROCm, GPU nodes, and rack-scale infrastructure, establishing deployment, reliability, and recovery practices. Optimize inference performance and capacity, debug issues across software and hardware layers, and build repeatable benchmarking, correctness, observability, and release-qualification systems.

Requirements

Requires at least five years of software engineering experience, substantial ownership of production systems, experience with production LLM or comparable GPU inference, strong C++ and Python skills, and hands-on experience with a high-performance serving framework. Candidates should understand GPU execution and distributed systems, have experience operating latency-sensitive services with Linux, containers, orchestration, observability, and CI/CD, and hold a bachelor’s degree in a related discipline or equivalent practical experience.

Skills

C++
Python
GPU Inference
vLLM
AMD ROCm
GPU Performance Optimization
Distributed Systems
Kubernetes
Linux
Model Serving
Performance Profiling
Continuous Batching
KV-Cache Management
Quantization
Numerical Validation
Production Reliability

Visa sponsorship

Not detected in the job text

Keywords

Cerebras Systems
GPU Inference
AMD Instinct
AMD ROCm
HIP
RCCL
vLLM
PyTorch
SGLang
TensorRT-LLM
Triton Inference Server
C++
Python
Kubernetes
Linux
Distributed Systems
Rack-Scale Infrastructure
Continuous Batching
Prefix Caching
KV-Cache
Tensor Parallelism
Expert Parallelism
RDMA
Quantization
BF16
FP8
GPU Kernel Optimization
Performance Profiling
Numerical Correctness
Inference Reliability

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Jobs in Canada