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Added 19 mins ago
TT
Senior Project Controller
Tetra Tech
Mississauga, ON
- Full-time
…essential duty satisfactorily. The requirements listed below are representative of the knowledge. Reasonable accommodations may be made to enable individuals with disabilities to perform…
Added 19 mins ago
BB
Field Technical Service Representative (Full Time)
Best Buy Canada
Langford, BC
- Full-time
You’ll love it here! We are hiring immediately for a field technical service representative, which at Best Buy we call a field service agent.
Added 19 mins ago
M
Sr. Technical Analyst, MarTech
Manulife
Toronto, ON
- Full-time
The MarTech Sr. Technical Analyst is responsible for supporting the implementation and maintenance of all digital analytics tools and Adobe Marketing technology integration for our Manulife…
Added 19 mins ago
M
Summer Intern 2027 - Marketing
Manulife
Toronto, ON
- Full-time
Work with development teams on technical implementation and product launches.
Added 19 mins ago
M
Winter Co-op 2027 - Software Engineering
Manulife
Waterloo, ON
- Full-time
…talented technology teams. You'll receive guidance from skilled technical leaders who value your teamwork and coordination abilities, and gain exposure to industry-leading, enterprise…
Added 1 hour ago
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Senior Bilingual Contracting Representative
BMO
Toronto, ON · YNG
- Full-time
…compensation rates so that payments are accurate and timely. Answers technical questions related to contracting and compensation…
Added 1 hour ago
BB
Associé(e) saisonnier(ère) des ventes au détail
Best Buy Canada
Gatineau, QC
- Part-time
Technical Service Representative: Set up and connect our customers’ devices in the store and in their homes, so they can enjoy their new tech right away. Must have a valid driver’s license.
Added 1 hour ago
H
Combined Lab & X-Ray Technologist Working Sup
HealthCareersInSask.ca
La Loche, SK
- Full-time
…physiological and pathological conditions. Coordinates and supervises technical staff and work processes in the lab and X-Ray departments. Performs various administrative…
Added 1 hour ago
H
Physician Assistant Degree
HealthCareersInSask.ca
Regina, SK
- Part-time
Commitment to a diverse, representative workforce and cultural safety
Added 1 hour ago
M
People Services AI Solutions & Configuration Lead
Manulife
Toronto, ON · Waterloo, ON
- Full-time
As People Services AI Solutions & Configuration Lead, you will serve as the technical configuration and solution design expert within our People Services AI squad. You will partner across…
Added 1 hour ago
M
Manager / Senior Manager, AI Model Risk Governance, Standards & Enablement
Manulife
Halifax, NS · Toronto, ON · Waterloo, ON · Montreal, QC
- Full-time
Support targeted oversight reviews, thematic assessments, and challenge activities requiring policy interpretation or technical expertise.
Added 1 hour ago
M
AVP, Corporate Development
Manulife
Toronto, ON
- Full-time
Strong communication skills, including ability to translate complex technical issues into fundamental concepts
Added 1 hour ago
M
Senior Solution Architect
Manulife
Toronto, ON
- Full-time
Conduct POCs, technical assessments, and feasibility studies to evaluate emerging technologies and solutions.
Added 1 hour ago
M
Winter Co-op 2027 - Business Technology
Manulife
Toronto, ON
- Full-time
Work with datasets to identify trends, generate insights, and create visual reports or dashboards that inform business and technical decisions.
Added 1 hour ago
SC
Housing Stability Worker - Indigenous Housing Specialist 62XXH
Starling Community Services
Kitchener, ON
- Full-time
…creates a supportive workplace environment. Starling Community Services (formerly Lutherwood) is a progressive, not-for-profit health and social service organization that strengthens…
Added 2 hours ago
MA
Technical sales representative
Maritime Auto Parts
Debert, NS
- From $32 CAD / hour
- Full-time
- On-site
Assess client’s needs and resources to recommend the appropriate goods or services
Added 2 hours ago
BS
Customer Focused Field Tech
BRUSSELL SERVICES LLC
Field, BC
- Full-time
The Technical Field Representative Apprentice is responsible for performing routine service calls and sales. The Technical Field Representative Apprentice is responsible for performing…
Added 2 hours ago
Retail Sales Representative - Antigonish NS
Eastlink
Antigonish, NS
Everyday there are opportunities to learn more about our products, services and promotions allowing you to excel in technical expertise
Added 2 hours ago
CS
Software sales representative
Catapult Social
Charlottetown, PE
- From $45,000 CAD / year
- Full-time
Advertise and/or promote products, sales or services
Added 3 hours ago
H
Physician Assistant Degree
HealthCareersInSask.ca
Saskatoon, SK
- Full-time
Commitment to a diverse, representative workforce and cultural safety
Added 3 hours ago
H
Medical Device Reprocessing Instrument Technician
HealthCareersInSask.ca
Regina, SK
- Part-time
Job Description: Provides technical expertise and acts as a liaison with the Operating Rooms (OR). Inspects, cleans, assembles, tests and sterilizes surgical instruments/ implants/equipment…
Added 3 hours ago
FS
Regional Sales Manager- Municipal- South Central Ontario
Federal Signal Corporation
Toronto, ON
- Full-time
The ideal candidate will bring strong technical knowledge, proven sales expertise, and the ability to recommend optimal equipment solutions that meet diverse municipal operational…
Added 3 hours ago
Alterations Specialist
David's Bridal
Cambridge, ON
…is responsible for exemplifying friendly, knowledgeable, and technical expertise and providing superior customer service. Alterations Specialists are members of the store team and…
Added 4 hours ago
H
Medical Radiation Technologist - Specialty
HealthCareersInSask.ca
Prince Albert, SK
- Full-time
Job Description: Performs a variety of specialized diagnostic technical procedures utilizing radiation equipment for the diagnosis and tracking of disease and pathology. Specialty…
Added 4 hours ago
Medical Radiation Technologist - Specialty
HealthCareersInSask.ca
Prince Albert, SK
Job Description: Performs a variety of specialized diagnostic technical procedures utilizing radiation equipment for the diagnosis and tracking of disease and pathology. Specialty…

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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