Jobs in Canada

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Added 4 months ago
K
Software Engineer II, AI
Klue
Toronto, Ontario
- $115,000 to $149,000 CAD / year
- Full-time
Contributions to open-source projects in the retrieval, NLP, or LLM ecosystems.
Added 4 months ago
SS
Intermediate Electrical Engineer
Sunbelt Solomon
Edmonton, Alberta
- Full-time
Reporting to the Operations Manager -the Intermediate Electrical Engineer will be accountable for executing projects through sound engineering expertise and project management, engaging in…
Added 3 months ago
C
Senior / Staff Software Engineer – Core Data Infrastructure
Calliere
Toronto, ON
- Full-time
Engineer robust storage solutions capable of handling rapidly expanding volumes of time-series and spatial data without compromising on query performance.
Added 4 months ago
SQ
Quantum Algorithms Engineer
SuperQ Quantum Computing
Remote, Canada
- Full-time
- Remote
…(specifically NVIDIA CUDA-Q), direct quantum hardware exposure, open-source contributions, or published work in QML or Quantum…
Added 4 months ago
PI
Software Engineer, Sportsbook Platform
PENN Interactive
Canada
- Full-time
NICE TO HAVE: building GraphQL APIs with Absinthe, hexagonal architecture, Domain Driven Development, contribution to open source software, experience working at startups, passion for…
Added 4 months ago
C
Senior Data Engineer
ClickUp
Canada
- Full-time
Contributions to open-source data tools or technical communities.
Added 3 months ago
HT
Research Engineer - AI Workload & Systems
Huawei Technologies Canada Co., Ltd.
Markham, ON
- Contract
Demonstrated research contributions through publications or influential open-source projects in AI infrastructure, systems, or computer architecture is an asset.
Added 3 months ago
AG
R2026-297 Senior Software Engineer
Adelphi Group
Toronto, ON
- Full-time
Contributions to open-source projects or strong technical community involvement.
Added 2 months ago
AN
BIOS Senior/Lead Software Engineer
Arista Networks
Vancouver, BC
- Full-time
…as well as keeping pace with the latest developments in the open source and proprietary BIOS development…
Added 3 months ago
AN
Expert/Principal Software Engineer
Arista Networks
Vancouver, BC
- Full-time
…and APIs. Working with, understanding and modifying existing open source software will be part of the role. An understanding of networking including L2 and L3 and switching ASICs will be…
Added 5 months ago
LA
AI Engineer
LGS, an IBM Company
Montreal, Quebec
- Full-time
Knowledge of LLM and LFM Models: Familiarity with proprietary models (OpenAI, Claude, Gemini, etc.) and open-source models on HuggingFace.
Added 4 months ago
S
Senior Backend & Infrastructure Engineer
Scispot
Remote, Canada
- $80,000 to $120,000 CAD / year
- Full-time
- Remote
We are looking for a senior backend and infrastructure engineer who treats production as a product.
Added 4 months ago
E
R&D Engineer
Eyeline
Vancouver, British Columbia
- Full-time
We are seeking an engineer who thrives at the intersection of research, open-source innovation, and production workflows. This role focuses on rapidly transforming novel research ideas,…
Added 2 months ago
A
Software Engineer (C++) - Platform & Emerging Technologies
Autodesk
Toronto, ON · Montreal, QC
- Full-time
Participation in open-source, academic, or personal software projects.
Added 4 months ago
SS
Electrical EIT
Sunbelt Solomon
Calgary, Alberta
- Full-time
Responsibilities of a Intermediate Electrical Engineer include aspects of technical expertise, engineering knowledge of electrical power systems for utilities, heavy industrial customers…
Added 4 months ago
Q
Senior Solution Engineer US/CAN based
Qovery
Canada
- Internship
Contribute when useful to Qovery’s open-source ecosystem (CLI, Terraform Provider, tooling).
Added 4 months ago
K
Senior Software Engineer, Agents
Klue
Vancouver, British Columbia
- $140,000 to $196,000 CAD / year
- Full-time
Interest in sharing learnings externally (blog posts, talks, open-source contributions).
Added 3 months ago
CS
Staff Software Engineer, GPU Inference
Cerebras Systems
Remote, Canada
- Full-time
- Remote
Experience modifying or contributing to vLLM, SGLang, PyTorch, Triton, TensorRT-LLM, or another open-source ML systems project.
Added 4 months ago
E
Senior Software Engineer
Epoch
Canada
- Full-time
Evaluate trade-offs between open-source vs hosted models and shape AI strategy
Added 4 months ago
TS
Automated Software Test Engineer
T-Rex Solutions
Remote, Canada
- $95,000 to $145,000 CAD / year
- Full-time
- Remote
Hands-on script development using JMeter or Gatling or other open source tools
Added 4 months ago
S
Senior Backend & Infrastructure Engineer
Scispot
Canada
- Full-time
We are looking for a senior backend and infrastructure engineer who treats production as a product.
Added 6 months ago
HC
Co-op Engineer - Compiler
Huawei Canada
Markham, Ontario
- Full-time
…applications while tackling technological challenges through open-source…
Added 5 months ago
X
Full Stack AI Engineer / Applied AI Engineer
Xsolla
Montreal, Quebec
- Full-time
Optimize backend systems for performance, scalability, and reliability.
Added 3 months ago
V
Manufacturing Engineer III
Verathon
Burnaby, BC
- Full-time
Verathon believes that People are the Source of our Strength! Employees that consistently demonstrate skill, loyalty, initiative, innovation, enthusiasm and team spirit are what make the…
Added 2 months ago
PI
Senior Software Engineer, Bet Engine
PENN Interactive
Canada
- Full-time
…are required to deliver without sacrificing the quality and performance we strive to maintain. This will include building a lot of cross-service integrations, with internal and external…

Cerebras Systems

Staff Software Engineer, GPU Inference

Remote, Canada

Remote

Full-time

Apply on jobs.ashbyhq.com About employer

Applications open in a new tab.

Job details

Job type: Full-time
Workplace: Remote
Remote eligibility: Canada listed. Check the posting for province restrictions.
Experience: 8+ years of software engineering experience, including substantial individual-contributor ownership of complex production systems.
Posting language: English
Posted: Jul 28, 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

8+ 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

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 on jobs.ashbyhq.com About employer

More about this job

Responsibilities

You will design, build, and maintain the GPU inference stack, ensuring high performance and reliability for large-scale AI workloads. Additionally, you will establish operational practices for the GPU fleet, including deployment, monitoring, and performance tuning across distributed systems.

Requirements

Candidates must have 8+ years of software engineering experience with a strong background in C++, Python, and production-grade GPU inference systems. A bachelor's degree in a technical field or equivalent practical experience is required, along with deep expertise in performance optimization and distributed systems.

Skills

C++
Python
GPU Inference
vLLM
PyTorch
ROCm
Distributed Systems
Performance Optimization
Kubernetes
Linux
Machine Learning Systems
Latency Optimization
Debugging
CI/CD
Observability
Parallelism

Visa sponsorship

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Keywords

GPU Inference
C++
Python
vLLM
PyTorch
ROCm
Distributed Systems
Kubernetes
Linux
Performance Profiling
Latency
Throughput
Tensor Parallelism
KV-cache
Quantization
HIP
CI/CD
Observability
AI Infrastructure
Large Language Models
Multimodal Models
GEMM
Attention Kernels
RDMA
Firmware
Driver Development
Software Engineering
Scalability
Numerical Correctness
Benchmarking

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Jobs in Canada