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Added 3 months ago
D
Software Engineer - Canada
DataVisor
Remote, Canada
- Full-time
- Remote
1-5 years experience in Java, Shell, Python development
Added 3 months ago
O
Senior Data Engineer
OMERS
Toronto, ON · Head Office Toronto
- Full-time
The Senior Data Engineer will join the Software Engineering team that leads the delivery of data and application solutions that enable OMERS Global Investments (GI) and Corporate teams to…
Added 4 months ago
S
RevOps Engineer
Studeo
Remote, Canada
- $80,000 to $120,000 CAD / year
- Full-time
- Remote
A GTM Engineer's Toolkit - Clay and n8n: You build. You've created Clay tables with real enrichment waterfalls, AI columns, API calls, and write-backs into a CRM - and you can show us one…
Added 4 months ago
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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
Senior Software Engineer - Backend
Evertz
Burlington, Ontario
- Full-time
We are seeking a highly motivated Senior Software Engineer to join our growing engineering team. This role offers an exciting opportunity to design and build scalable, production grade…
Added 4 months ago
E
Embedded Software Engineer
Evertz
Burlington, Ontario
- $60,000 to $90,000 CAD / year
- Full-time
We're looking for a passionate Embedded Software Engineer to join our development team, where you'll play a key role in designing, implementing, and maintaining embedded software for…
Added 4 months ago
SI
R&D Engineering, Staff Engineer
Synopsys Inc
Vancouver, British Columbia
- Full-time
…numerical choice you made last week, and you are the kind of engineer who sees that choice…
Added 4 months ago
C
Jr Data Engineer - Custom Solutions
Citylitics
Toronto, Ontario
- $70,000 to $80,000 CAD / year
- Full-time
We're looking for a skilled and enthusiastic Junior Data Engineer to join our growing team! We're a close-knit group building and maintaining mission-critical data products, and we need…
Added 4 months ago
K
Senior Software Engineer, Agents
Klue
Vancouver, British Columbia
- $140,000 to $196,000 CAD / year
- Full-time
We're looking for a Senior Software Engineer to join our team in Vancouver, someone excited to build and optimize state-of-the-art LLM-powered agents at scale. You'll bring a builder's…
Added 3 months ago
Forward Deployed Engineer, Supply Chain
Jetson Home
North Vancouver, BC
We're building a new kind of role to help us scale: the Forward Deployed Engineer (FDE). The title was originally coined for engineers embedded with external customers, and we've pointed…
Added 3 months ago
AG
Data Scientist (ML Engineer)
Adelphi Group
Toronto, ON
- Full-time
As a Data Scientist (ML Engineer), on the Perpetua team, you will design, experiment with, and ship the machine learning systems that decide how thousands of brands spend their advertising…
Added 2 months ago
Modern Workplace Engineer - Intune & Endpoint Management
Scotiabank
Toronto, ON · Scarborough, ON
The Role: Intune Automation Engineer - AI & Modern Workplace
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
S
Senior Data Engineer
ShyftLabs
Toronto, ON
- Full-time
ShyftLabs is seeking an experienced Senior / Lead Data Engineer to lead the design, architecture, and delivery of enterprise-scale data platforms for Fortune 500 organizations. This is a…
Added 2 months ago
J
Senior Software Engineer, Applied AI (Toronto)
Justworks
Toronto, ON
- $188,000 to $242,000 CAD / year
We are seeking a Senior Software Engineer with a strong passion for building AI-native systems in a product environment. The ideal candidate will be able to take ownership of large segments…
Added 3 months ago
VG
Software Engineer - Team Lead (Forward Deployed)
Volaris Group
Mississauga, ON · Canada - Mississauga, ON
- Full-time
We’re looking for a Software Engineer Team Lead (Forward Deployed) to join our customer engineering team as a player/coach. You’ll work directly with enterprise clients to design,…
Added 3 months ago
Q
Sr. Engineer, Machine Learning Software Verification
Qualcomm
Markham, ON
- Full-time
1+ years of Python and other scripting programming
Added 1 month ago
A
Test/Lab Engineer
Actalent
Oakville, ON
- Contract
Our client in the automotive industry, is looking to hire a Test/Lab Engineer.
Added 4 months ago
F
AI Full Stack Engineer
Feathery
Toronto, Ontario
- $90,000 to $140,000 CAD / year
- Full-time
To keep pace with that ambition, we're looking for a Full Stack Engineer to join the AI team and own these capabilities end-to-end.
Added 4 months ago
T
Senior QA Automation Engineer
Tubi
Toronto, Ontario
- Full-time
Tubi is seeking a highly skilled and experienced Senior QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This…
Added 4 months ago
I
Senior AI Software Engineer
iManage
Toronto, Ontario
- Full-time
Being a Senior AI Software Engineer at iManage Means
Added 4 months ago
O
Application Security Engineer
Opendoor
Toronto, Ontario
- Full-time
As our Application Security Engineer, you'll own how we find, prioritize, and drive down application-layer risk across the consumer flows that put cash offers in homeowners’ hands, the…
Added 3 months ago
B
Senior Consultant, Migration Engineer
BDO
Toronto, ON
- Full-time
At BDO, our purpose is helping people thrive. As a Senior Consultant, Migration Engineer, you will join a growing team focused on helping organizations modernize their technology…
Added 3 months ago
A
Sr Associate Software Engineer - Applied AI
Amgen
Burnaby, BC
- Full-time
As a Sr Associate Software Engineer, you will be an integral member of the Applied AI – AI Productivity/Custom GPT Solutions Practice team, which empowers Amgen teams and staff members to…

Cerebras Systems

Staff Software Engineer, GPU Inference

Remote, Canada

Remote

Full-time

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Job details

Job type: Full-time
Workplace: Remote
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.

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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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