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Added 22 mins ago
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Senior Naval Architect - Team Lead
BMT
Victoria, BC
- $105,000 to $150,000 CAD / year
- Full-time
Conduct performance personnel reviews for direct reports, including establishment of Personal Development Plans (PDPs).
Added 22 mins ago
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Senior Naval Architect - Team Lead
BMT
Ottawa, ON
- $105,000 to $150,000 CAD / year
- Full-time
Conduct performance personnel reviews for direct reports, including establishment of Personal Development Plans (PDPs).
Added 22 mins ago
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Senior Naval Architect - Team Lead
BMT
Dartmouth, NS
- $105,000 to $150,000 CAD / year
- Full-time
Conduct performance personnel reviews for direct reports, including establishment of Personal Development Plans (PDPs).
Added 52 mins ago
VC
Design Coordinator
VINCI Construction Grands Projets Hellas S.A.
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Monitor progress and performance of technical activities, taking appropriate action when needed
Added 1 hour ago
AC
D365 F&O Functional Analyst
Aston Carter
Richmond, BC
- Full-time
Monitor and maintain overall environment health to ensure reliable system performance and availability.
Added 2 hours ago
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Lead Software Engineer
Virtusa
Toronto, ON
- Full-time
Support financial performance analysis and ensure compliance with organizational standards.
Added 2 hours ago
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Senior Software Engineer
Virtusa
Toronto, ON
- Full-time
Lead cross-functional engineering, QA, and product teams, removing technical blockers and fostering high performance.
Added 2 hours ago
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Senior Project Manager
Virtusa
Toronto, ON
- Full-time
Job Summary: We are seeking a highly skilled Data Engineer with extensive experience in agentic frameworks and generative AI. The ideal candidate will be responsible for designing and…
Added 3 hours ago
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Expert Engine Engineer - Treyarch - Vancouver, BC
Activision
Vancouver, BC
- Other
Treyarch, the studio behind the best-selling Call of Duty: Black Ops franchise, is seeking an Expert Engine Engineer to join our Core Engine team. This is an opportunity to help shape the…
Added 3 hours ago
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Senior Engine Engineer - Treyarch - Vancouver, BC
Activision Blizzard, Inc.
Vancouver, BC
- Full-time
Treyarch, the studio behind the best-selling Call of Duty: Black Ops franchise, is seeking an Senior Engine Engineer to join our Core Engine team. This is an opportunity to help shape the…
Added 3 hours ago
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Full Stack Engineer (AI-Enabled)
BMO
Calgary, AB · GCS
- Full-time
We are looking for a Full Stack Engineer who can design and deliver scalable, enterprise-grade solutions while building AI capabilities directly into our platforms.
Added 3 hours ago
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Developer Lead (AI-Enabled Systems)
BMO
Toronto, ON · FCP
- Full-time
We are looking for a Full Stack Engineer who can design and deliver scalable, enterprise-grade solutions while building AI capabilities directly into our platforms.
Added 4 hours ago
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Building Maintenance Mechanic
Saputo Inc.
Mississauga, ON
- Full-time
Engineer high‑quality semantic models (datasets) optimized for performance, reusability, and enterprise reporting
Added 5 hours ago
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Lead Software Engineer
Virtusa
Toronto, ON
- Full-time
…collaborate with cross-functional teams to enhance product performance and drive…
Added 5 hours ago
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Lead Software Engineer
Virtusa
Toronto, ON
- Full-time
Job Summary: We are seeking a highly skilled QA Automation Engineer with 7-10 years of experience to join our dynamic team in Toronto. The ideal candidate will play a crucial role in…
Added 5 hours ago
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Lead Software Engineer
Virtusa
Toronto, ON
- Full-time
Job Summary: We are seeking a highly skilled QA Automation Engineer with 7-10 years of experience to join our dynamic team in Toronto. The ideal candidate will play a crucial role in…
Added 5 hours ago
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Lead Software Engineer
Virtusa
Toronto, ON
- Full-time
Conduct downstream testing to ensure data integrity and system performance.
Added 5 hours ago
AI
Applications Engineering Manager, Nuclear
ATS Industrial Automation
Cambridge, ON
- Full-time
…strengthens ATS differentiation, cost competitiveness, and margin performance. The role also defines, monitors, and reports key performance indicators, leads and develops a geographically…
Added 5 hours ago
A
Senior Engine Engineer - Treyarch - Vancouver, BC
Activision
Vancouver, BC
- Full-time
Treyarch, the studio behind the best-selling Call of Duty: Black Ops franchise, is seeking an Senior Engine Engineer to join our Core Engine team. This is an opportunity to help shape the…
Added 5 hours ago
V
Lead Software Engineer
Virtusa
Toronto, ON
- Full-time
Job Summary: We are seeking a highly skilled QA Automation Engineer with 7-10 years of experience to join our dynamic team in Toronto. The ideal candidate will play a crucial role in…
Added 5 hours ago
AI
Engineering - Flight Software Engineer
Aversan Inc.
Brampton, ON
- $112,000 to $140,000 CAD / year
- Full-time
We are currently seeking a qualified Senior Flight Software Engineer/MTS to join our team. In this role, you will lead designs for safety critical, real-time software solutions while…
Added 6 hours ago
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Ingenieur Qualité - Conception Biomedical
Actalent
Montreal, QC
- $45 to $70 CAD / hour
- Contract
Mener la gestion des risques en lien avec le processus médical, en évaluant systématiquement les impacts des décisions de conception sur la sécurité et la performance clinique.
Added 6 hours ago
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Manager, Bridges and Structures- BC
CN
Kamloops, BC
- Full-time
Minimum 7 years of railroad bridge experience
Added 6 hours ago
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IC/FPGA Design Verification Engineer, Sr Staff
Qualcomm
Ottawa, ON
- Full-time
…create a smarter, connected future for all. As a Qualcomm ASIC Engineer, you will define, model, design (digital and/or analog), optimize, verify, validate, implement, and document IP…
Added 7 hours ago
TT
CNC Machining Centre Programmer
Titan Trailers Industries Limited - UK
Tillsonburg, ON
- Full-time
Experience with 3d modeling programs such as Creo/Pro Engineer, AutoCAD inventor, solidworks, Rhino, Sketchup, Catia an asset.

Cerebras

Software Engineer, GPU Inference

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 8, 2026
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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