Jobs in Canada

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Added 4 months ago
WI
Junior Geotechnical Engineer-in-Training
WSP in Canada
Terrace, British Columbia
- Volunteer
Build the Future with Us – We are seeking a highly motivated Junior Geotechnical Engineer-in-Training to join our northern BC & Yukon – Ground Engineering team in the city of Terrace, BC.…
Added 4 months ago
WI
Junior Geotechnical Engineer-in-Training
WSP in Canada
Terrace, British Columbia
- Volunteer
Build the Future with Us – We are seeking a highly motivated Junior Geotechnical Engineer-in-Training to join our northern BC & Yukon – Ground Engineering team in the city of Terrace, BC.…
Added 5 months ago
J
Lead Marketing Data & Analytics Engineer
Jetson
North Vancouver, British Columbia
- Full-time
Added 4 months ago
RV
Manager, FPGA & Hardware Development
Ross Video
Nepean, Ontario
- Full-time
…agreed feature set. Liaise with the Manufacturing, Manufacturing Test Engineering, and Tech Support to enable smooth product sales & order process, build of required hardware/software…
Added 2 months ago
P
Senior Systems Engineer (Woodbridge, ON)
PerkinElmer
Woodbridge, ON
- Full-time
In this role, the Systems Design Engineer will become an integral part of a team that will design, develop, and integrate complex hardware systems for every stage of PerkinElmer’s Gas…
Added 2 months ago
EI
Manufacturing Engineer
Ecolab Inc.
Calgary, AB
- Full-time
We have an opportunity for a Manufacturing Engineer to join our team in Calgary, Alberta. In this role, you will work closely with our manufacturing and design teams as well as our…
Added 2 months ago
A
Software Engineer (C++) - Platform & Emerging Technologies
Autodesk
Toronto, ON · Montreal, QC
- Full-time
Software Engineer (C++)– Platform & Emerging Technologies
Added 3 months ago
E
Manufacturing Engineer
Ecolab
Calgary, AB · CAN-Calgary Office Quarry Park
- Full-time
We have an opportunity for a Manufacturing Engineer to join our team in Calgary, Alberta. In this role, you will work closely with our manufacturing and design teams as well as our…
Added 3 months ago
D
Software Engineer - Canada
DataVisor
Remote, Canada
- Full-time
- Remote
Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive,…
Added 2 months ago
Sr. Functional Safety Engineer
Dana Incorporated
Boucherville, QC
The Sr. Functional Safety Engineer supports the delivery of ISO 26262 functional safety activities across electrified
Added 4 months ago
C
Senior API Automation Test Engineer
Cognizant
Toronto, Ontario
- $65,000 to $90,000 CAD / year
- Full-time
Must have strong proficiency in Java programming · Must have 2+ years of exp
Added 4 months ago
B
Senior Software Engineer - Product (Toronto)
Bite
Remote, Canada
- $140,000 to $200,000 CAD / year
- Full-time
- Remote
We expect every engineer here to be genuinely fluent with AI coding tools - not as a novelty, but as a core part of the daily workflow. Whether that's agentic coding, AI-assisted refactors,…
Added 4 months ago
GN
Director of Conversion Rate Optimization (CRO)
Ground News
Remote, Canada
- Full-time
- Remote
Onboarding & In-App Optimization: Architect, test, and refine the mobile app onboarding sequence and in-app purchase (IAP) funnels to maximize user activation and initial paywall conversion.
Added 4 months ago
E
evTOC Applications Engineer
Evertz
Burlington, Ontario
- Full-time
Work experience in a similar or related field – Software Validation, Quality Assurance (QA), Hardware Validation, System Test Engineering
Added 4 months ago
E
FPGA Design Engineer
Evertz
Burlington, Ontario
- Full-time
The FPGA Design Engineer at Evertz contributes to the development of advanced broadcast equipment used in real-time video and audio production, processing, and transport for Live sports…
Added 4 months ago
E
DSP Engineer (Markham)
Evertz
Markham, Ontario
- Full-time
…maintain codes running on FPGA and other heterogeneous platforms, test, debug and refine…
Added 4 months ago
E
Junior FPGA Design Engineer
Evertz
Markham, Ontario
- Full-time
Collaborate closely with other hardware and software engineers to test and debug the design
Added 4 months ago
E
Embedded Software Engineer
Evertz
Burlington, Ontario
- $60,000 to $90,000 CAD / year
- Full-time
Must possess a degree in Electrical/Computer/Mechatronics Engineering or Computer Science
Added 4 months ago
U
Tech Lead, Software Development
Univeris
Toronto, Ontario
- $100,000 to $130,000 CAD / year
- Full-time
At Univeris, a Software Development Technical Team Lead is a hands-on senior software engineer and people manager, accountable for the technical design, development, quality of…
Added 4 months ago
SI
R&D Engineering, Staff Engineer
Synopsys Inc
Vancouver, British Columbia
- Full-time
You have spent years working at the boundary where Maxwell's equations meet real software, and you know that getting electromagnetic simulation right means understanding both the physics…
Added 5 months ago
BC
Electrical Engineer
British Columbia Rapid Transit Company
Vancouver, British Columbia
- Full-time
…cause analysis and presents reports/recommendations to Senior Engineer and Principal Engineer. Assists in the development of FMEA and FMECA where required. Ensures effective communication…
Added 3 months ago
CS
Staff Software Engineer, GPU Inference
Cerebras Systems
Remote, Canada
- Full-time
- Remote
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…
Added 2 months ago
Staff Software Engineer (Platform)
Dialpad
Kitchener, ON
As a Staff Software Engineer, you’ll own the platformization roadmap for shared services, architecting a plan to decouple existing functionality into highly reusable services. Your…
Added 3 months ago
W
Senior Systems Engineer
Weir
Montreal, QC · Ottawa, ON · Gatineau, QC · Dartmouth, NS
- Full-time
…the impact of new information from stakeholders on the design/test work in progress, and coordinate with information systems subject matter experts who will perform IT detailed design and…
Added 3 months ago
Q
Sr. Engineer, Machine Learning Software Verification
Qualcomm
Markham, ON
- Full-time
AI’s ability to solve complex problems across multiple domains is transformative. In the AI Software team, we build the Qualcomm AI Engine direct to enables OEMs and developers to run their…

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

Not detected in the job text

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