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Added 11 mins ago
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Graduate Mechanical Engineer
Worley
Vancouver, BC · Edmonton, AB · Calgary, AB
- Full-time
Added 11 mins ago
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Principal Mechanical Engineer
Worley
Oakville, ON
- Full-time
We are currently recruiting for a Principal Mechanical Lead Engineer (MMM). Our team includes world class experts and dynamic go-getters. This is a full-time position based in Oakville,…
Added 11 mins ago
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Senior Software Engineer
Microsoft
Vancouver, BC
- Full-time
As a Senior Software Engineer on the IC3 AEGIS team, you will design and build an AI-driven platform supporting centralized security automation and risk remediation. You will develop…
Added 11 mins 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 26 mins ago
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Intermediate Civil Engineer
Ausenco
Vancouver, BC
- Full-time
Our team in Canada is growing! We are currently recruiting for an Intermediate Civil Engineer to join our Project Delivery team in our Minerals and Metal Business line in the Vancouver…
Added 26 mins ago
Senior Data Engineer
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Toronto, ON
…and optimize that movement. We're looking for a Senior Data Engineer to design, build, and scale the data infrastructure that powers logistics operations, transportation analytics,…
Added 41 mins ago
IG
Senior Software Engineer
Infotree Global Solutions
Canada
- Contract
Seeking a highly motivated Senior Software Engineer on a contract basis to contribute to strategic initiatives in "supply chain security" and "cloud-native security".
Added 41 mins ago
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Senior Software Engineer
Strive Robotics
Toronto, ON · Greater Toronto Area, Canada
- Full-time
We are looking for a senior software engineer to build the software platform through which AI agents understand, configure, execute, and improve physical workflows. You will work across…
Added 41 mins ago
SR
Robotics Engineer
Strive Robotics
Toronto, ON · Greater Toronto Area, Canada
- Full-time
We are looking for an early-career engineer who wants to build robots that perform real manufacturing work. You will contribute to manipulation, controls, perception, planning, and…
Added 41 mins ago
SR
Software Engineer
Strive Robotics
Toronto, ON · Greater Toronto Area, Canada
- Full-time
We are looking for an early-career engineer who wants to build software that connects AI systems to physical work. You will contribute to AI agents, workflow tools, and evaluation systems…
Added 41 mins ago
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Senior Robotics Engineer
Strive Robotics
Toronto, ON · Greater Toronto Area, Canada
- Full-time
We are looking for a senior robotics engineer to own major parts of the intelligence and control stack for robots performing complete manufacturing workflows. You will work across…
Added 41 mins ago
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Senior Android Engineer – Mobile Design Systems
Diligente Technologies
Canada
- Contract
Seeking a Senior Android Engineer with 5+ years of native Android development experience to build and evolve scalable mobile Design Systems and reusable UI components. The ideal candidate…
Added 41 mins ago
FI
QA Analyst
Fellow Insights Inc.
Remote, Canada
- Full-time
- Remote
A QA Engineer focused only on automation. Automation experience matters here, but the center of the role is manual QA and holistic testing.
Added 56 mins ago
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Software Engineer
Found People Inc.
Toronto, ON
- $110,000 to $140,000 CAD / year
- Full-time
Added 56 mins ago
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Operating Engineer
Mackenzie Health
Richmond Hill, ON
- $38.73 CAD / hour
- Part-time
Adhering to established standards, procedures and policies, the Engineer ensures that the boilers and related equipment is functioning effectively, in order to provide a safe, comfortable…
Added 1 hour ago
CI
Ingénieur mécanique principal / Senior Mechanical Engineer
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Vaudreuil-Dorion, QC
- Full-time
We are currently seeking a candidate for the position of Senior Mechanical Design Engineer. The successful candidate will lead the design, analysis, development, production, maintenance and…
Added 1 hour ago
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Machine Learning Engineer Intern
Workday
Toronto, ON · Vancouver, BC · Canada, BC, Vancouver
- Full-time
As a Machine Learning Engineer Intern, you’ll help develop Workday’s intelligent core by contributing to the scalable AI and ML platforms that power personalized experiences for millions of…
Added 1 hour ago
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Software Development Engineer Intern
Workday
Vancouver, BC · Canada, BC, Vancouver
- Full-time
As a Software Development Engineer Intern, you will jump right into building real-world solutions and experience what it's like to be a developer at Workday. You'll work closely with a team…
Added 1 hour ago
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Machine Learning Engineer, AI Processors (Sr to Staff)
Qualcomm Innovation Center, Inc.
Markham, ON
- Full-time
We are seeking a talented Machine Learning Engineer to join the Qualcomm AI Processor Solutions team, where you will help develop next-generation AI applications for Qualcomm Snapdragon…
Added 1 hour ago
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Mechanical Building Engineer
BPA
Toronto, ON
- Full-time
Are you ready to make an impact in Toronto’s dynamic building industry? BPA is seeking a Mechanical Building Engineer passionate about delivering innovative mechanical systems, with a focus…
Added 1 hour ago
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Principal Rock Mechanics Engineer
Kinross Gold Corporation
Toronto, ON
- Full-time
The Principal Rock Mechanics Engineer serves as the Company's senior technical specialist and subject matter expert for underground rock mechanics, geotechnical risk management, ground…
Added 1 hour ago
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Staff ASIC Verification Engineer, Low Power AI
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Markham, ON
- Full-time
We are looking for a Staff ASIC Verification Engineer to be part of our team to innovate and design complex leading, ultra-low power, solutions for audio and AI/context aware applications.
Added 1 hour ago
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Senior Execution Engineer
Enbridge
Regina, SK · Sherwood Park, AB · Calgary, AB
- Full-time
…innovation, and asset reliability. We are seeking a Senior Execution Engineer to join our…
Added 1 hour ago
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Senior Software Engineer (Frontend), Search
Scribd, Inc.
Toronto, ON · Vancouver, BC
- Full-time
Added 1 hour ago
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Associate, Client Engineering (Mexico City)
Glia
Vancouver, BC
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As part of our Entry Client Engineer Team, you'll help our customers to resolve complex technical problems, providing proactive guidance, and adding value through the use of Glia’s…

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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