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Added 24 mins ago
Q
Mechanical Engineer
Quectel
Vancouver, BC
- Full-time
Quectel North America is looking for a Mechanical Engineer to own product structure from concept through mass production. You will lead structural and stack-up design for consumer…
Added 25 mins 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 25 mins ago
Senior Backend Engineer II - Patient Experience
Prenuvo
Vancouver, BC
…non-invasive (no contrast). Our unique integrated stack of optimized hardware, software, and increasingly AI, coupled with the patient-centric experience across our domestic and global…
Added 40 mins ago
Sr. Staff Engineer, IP Runtime
Tenstorrent
Toronto, ON
You will work at the hardware/software boundary to define how those hardware blocks are initialized, coordinated, and used by the runtime. You will determine how workloads are dispatched,…
Added 54 mins ago
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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…
Added 54 mins ago
RL
Optical Engineer II
Rocket Lab
Toronto, ON
- Full-time
…reach to the Moon, Mars, and beyond. We move fast, build real hardware for meaningful missions, and make the impossible routine. Come shape the future with…
Added 1 hour ago
W
Staff Vehicle Program Manager
Waabi
Toronto, ON
- Full-time
Waabi is adding OEM partners, and each partnership needs an engineer who owns the technical integration from program setup to on-road milestones. The Vehicle Program Manager is Waabi's…
Added 1 hour ago
CM
Propulsion Engineer
Carter Murray
Montreal, QC
- $75,000 to $150,000 CAD / year
- Full-time
Our client is seeking a Propulsion Engineer to support commercial aircraft engine maintenance, repair, and overhaul (MRO) operations, with a primary focus on CFM56 engines. This role is…
Added 1 hour ago
RL
Lead, Manufacturing Engineer
Rocket Lab
Toronto, ON
- Full-time
…reach to the Moon, Mars, and beyond. We move fast, build real hardware for meaningful missions, and make the impossible routine. Come shape the future with…
Added 1 hour ago
R
SCADA Transmission Engineer
Raise
Burnaby, BC
- Full-time
The SCADA Transmission Engineer to join our clients team and play a key role in delivering complex, multi-discipline capital projects. In this role, your primary focus will be delivering…
Added 1 hour ago
TV
Technical Business Development Director
TandemLaunch Ventures Studio & Funds
Montreal, QC
- Full-time
…$700M. We commercialize innovations in consumer electronics, hardware-enabled technologies, machine learning, and embedded systems, working directly with researchers from major university…
Added 1 hour ago
TV
Director of Product Strategy and Commercialization
TandemLaunch Ventures Studio & Funds
Montreal, QC
- Full-time
…$700M. We commercialize innovations in consumer electronics, hardware-enabled technologies, machine learning, and embedded systems, working directly with researchers from major university…
Added 1 hour ago
Internship, IT Technician
Pomerleau
Vancouver, BC
Diagnose and resolve hardware, software, network connectivity, and other technical issues.
Added 1 hour ago
Directeur de la stratégie produit et de la commercialisation | Director of Product Strategy and Commercialization
TandemLaunch
Montreal, QC
Added 2 hours ago
VL
Client Engagement Lead - Canada
Very LLC
Remote, Canada
- Full-time
- Remote
Bachelor's degree in Engineering (or equivalent hands-on experience) and time spent working as a practicing engineer earlier in your career
Added 2 hours ago
ZT
Développeur de logiciels, professionnel II/ Software Engineer, Professional II
Zebra Technologies
Montreal, QC · CAN - Montreal, Canada
- Full-time
…software that directly controls and integrates with advanced hardware. You will utilize a modern tech stack featuring a React-based web frontend and a robust C# .NET backend. This system…
Added 2 hours ago
A
Senior Software Engineer / Member of Technical Staff (MTS)
Akkodis
Brampton, ON
- Contract
Position: Senior Software Engineer / Member of Technical Staff (MTS)
Added 2 hours ago
ES
Software Engineer Intern (Summer 2027 - 8-Months - Sports Technology - Undergraduate)
EA SPORTS
Vancouver, BC
- Temporary
…developed can apply to many different engines, environments, and hardware platforms. You will work on our strategic, multi-year projects focused on user-generated experiences, improved…
Added 2 hours ago
A
IOHUB Design Verification Engineer
AMD
Markham, ON
- $128,000 to $192,000 USD / year
- Full-time
Solid knowledge of hardware verification methodologies, including coverage-based verification, hardware assertions such as PSL or SVA, and constrained-random techniques.
Added 3 hours ago
Associate Technical Services Engineer II
MongoDB
Toronto, ON
If you have an operations background, we prefer experience administering large-scale production environments, including hardware, operating systems (e.g. Linux, Windows), networks…
Added 4 hours ago
Software Engineer Intern (Summer 2027 - 8-Months - Sports Technology - Undergraduate)
Electronic Arts
Vancouver, BC
…developed can apply to many different engines, environments, and hardware platforms. You will work on our strategic, multi-year projects focused on user-generated experiences, improved…
Added 4 hours ago
SA
Staff Software Engineer, Teleoperation
Sanctuary AI
Vancouver, BC
- Full-time
Sanctuary AI is hiring a Staff Software Engineer to drive and evolve the production teleoperation and data collection software that enables robot operators to control robots.
Added 4 hours ago
M
Software Developer, Robotic Data & Deliveries
Mecka
Richmond Hill, ON
- $150,000 to $200,000 USD / year
- Full-time
We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and…
Added 4 hours ago
HR
Signaling System Engineer
Hitachi Rail
Mississauga, ON
- Full-time
Hitachi Rail is looking an enthusiastic and self-motivated Signaling System Engineer who thrives in a fast paced environment. This role located on-site in Mississauga, Ontario CA.
Added 5 hours ago
L
IT Desktop Engineer - Co-Op/Intern
Lumentum
Ottawa, ON · Canada - Ottawa (Bill Leathem)
- Full-time
Position Title: IT Desktop Engineer – Co-Op/Intern

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.

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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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