Jobs in Canada

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Added 1 month ago
Engineer MW5/SE4
Fraser Health
Chilliwack, BC
We currently have an exciting opportunity for a Casual Engineer MW5/SE4 at Chilliwack General hospital located in Chilliwack, British Columbia.
Added 1 month ago
Integration Engineer - SHIFT
Mariner
Saint John, NB
Translate mechanical system behavior, equipment setup and control sequences, and reconcile them with EOS optimizations to ensure seamless integration and operations.
Added 1 month ago
E
Field Service Engineer
Ecolab
Calgary, AB · CAN-Calgary Office Quarry Park
- Full-time
Must hold a valid driver’s license and passport and be eligible to pass security checks for customer sites
Added 1 month ago
Traffic Engineer (East), Pacific Link (Contract)
Trans Mountain
Calgary, AB
Must have a valid Class 5 driver’s license
Added 1 month ago
Traffic Engineer (West), Pacific Link (Contract)
Trans Mountain
Calgary, AB
Must have a valid Class 5 driver’s license
Added 1 month ago
ED
Sr Software Developer (Lead) - EN 178
Export Development Canada | Exportation et développement Canada
Vancouver, BC
- $96,557 to $128,743 CAD / year
- Full-time
Export Development Canada operates in a hybrid work environment, currently requiring employees to work in the office 3 days per week
Added 1 month ago
A
Electrical EIT
Actalent
Calgary, AB
- $25 to $28 CAD / hour
- Contract
Create cable schedules and power system designs.
Added 1 month ago
CI
Lead software engineer
Cogency Inc
Toronto, ON
- From $57 CAD / hour
- Full-time
- On-site
Evaluate the performance and reliability of system designs
Added 1 month ago
CB
Marine Electricians (Journeyperson Electrician)
Cape Breton Job Board
North Sydney, NS
- Full-time
The vessel crew members must have a clear understanding of the Muster list, emergency duties, Vessel Emergency Plan and SOLAS training manual · Must have knowledge of a delta distribution system
Added 1 month ago
GO
Power Engineer
Government of Manitoba
Selkirk, MB
- Full-time
Must have a valid Manitoba Class 5 Driver's Licence · Must have minimum valid 3rd Class Power Engineering Certificate recognized by the Office of the Fire Commissioner
Added 1 month ago
MC
Mechanical Commissioning Associate
Mission Critical Engineers | Mission Critical Forensics
Regina, SK
- Full-time
…Associate will work alongside the Lead Data Centre Commissioning Engineer & Project Manager and the commissioning team during system startup, test preparation, functional testing,…
Added 1 month ago
MC
Mechanical Commissioning Associate
Mission Critical Engineers | Mission Critical Forensics
Regina, SK
- Full-time
…Associate will work alongside the Lead Data Centre Commissioning Engineer & Project Manager and the commissioning team during system startup, test preparation, functional testing,…
Added 1 month ago
KA
Aircraft Maintenance Engineer - Structures Licensed
KF Aerospace
Kelowna, BC
- $38.03 to $45.65 CAD / hour
- Full-time
Modified work schedule, working 4 days per week/10 hours per day
Added 1 month ago
W
Concepteur électrique / Electrical Designer
Wabtec
Montreal, QC
- Full-time
Added 1 month ago
X
Computer network technician
Xiingo
Mississauga, ON
- From $41 CAD / hour
- Full-time
- On-site
Evaluate and install computer hardware, networking software and operating system software
Added 1 month ago
C
Project Coordinator - Candidate Pool
CIMA+
Calgary, AB
- $92,800 to $127,600 CAD / year
- Full-time
…what’s expected of us to meet the challenges of tomorrow and engineer a better…
Added 1 month ago
C
Project Manager - Candidate Pool
CIMA+
Calgary, AB
- $110,480 to $151,910 CAD / year
- Full-time
…what’s expected of us to meet the challenges of tomorrow and engineer a better…
Added 1 month ago
A
Software Dev Engineer, AFFS - ARS (Amortization Runtime Subledger)
Amazon
Vancouver, BC
- Full-time
As a Software Development Engineer, you'll design massively scalable distributed systems handling complex financial workflows. You'll work on services requiring low latency, high…
Added 1 month ago
I
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
O(
Quality Engineer - 6-month contract
OTIP (Ontario Teachers Insurance Plan)
Waterloo, ON
- Contract
Reporting to the Senior Manager, DevOps & System Integration, the Quality Engineer is responsible for creating, reviewing, executing, and documenting the tests necessary to ensure that…
Added 1 month ago
GD
Software Test Specialist/Engineer
General Dynamics Land Systems–Canada
London, ON
- Full-time
…and how the software test plans are integrated with overall system verification…
Added 1 month ago
SE
Lead RTL Engineer
Schweitzer Engineering Laboratories (SEL)
Burnaby, BC · Canada - Burnaby
- $105,600 to $158,400 CAD / year
- Full-time
Schweitzer Engineering Laboratories (SEL) is hiring a Lead Engineer with a focus in VHDL Register-Transfer Level (RTL) Digital Logic design for our R&D Communications product group. In this…
Added 1 month ago
A
Associate Quality Engineer - Point of Care (Ottawa)
Abbott
Ottawa, ON
- $59,250 to $86,900 CAD / year
- Full-time
Familiarity with Statistical Process Control (SPC), Corrective and Preventive Action (CAPA), Root Cause Analysis (RCA), Failure Mode and Effects Analysis (FMEA), and quality management…
Added 1 month ago
Sr. Staff Engineer, IP Runtime
Tenstorrent
Toronto, ON
An expert C or C++ engineer with a track record of designing and delivering complex, performance-critical systems.
Added 1 month ago
C
Software Engineer, GPU Inference
Cerebras
Toronto, ON
- Full-time
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…

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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Work requirements

Jobs in Canada