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Added 3 months ago
HP
Tecoustics - Technical Production Designer
HR Performance & Results
Remote, Canada
- $65,000 CAD / year
- Full-time
- Remote
Do you take pride in getting every detail exactly right and are the kind of person a design or drawing that’s 99% correct still bothers?
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 3 months ago
SC
Staff Analog Design Engineer
SiTime Corporation
Ottawa, ON
- $114,210 to $157,040 CAD / year
- Full-time
SiTime is looking for a Staff Analog Design Engineer to join a talented analog design team developing advanced clock and timing products. You will lead the development of key circuit blocks…
Added 3 months ago
SC
Senior Staff Analog Design Engineer
SiTime Corporation
Ottawa, ON
- $130,500 to $186,620 CAD / year
- Full-time
SiTime is seeking a Senior Staff Analog Design Engineer to provide technical leadership in developing advanced clock and timing products. This role combines hands-on circuit design…
Added 4 months ago
E
Software Engineer II, EMR Platform
Experity
Chiasson Office, NB
- Full-time
Be responsible for the design, development, maintenance, and support of custom .NET applications which includes the development and modification of frontend and backend code.
Added 4 months ago
T
Senior Automation Engineer
Tubi
Toronto, Ontario
- Full-time
…coverage, and contribute to the efficiency of our multi-platform release process. You will also design data-driven end-to-end checks around playback and ad insertion , integrate them into…
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
E
Senior UI Engineer I
EBizCharge
Canada
- Full-time
As a Senior UI Engineer I at EBizCharge, you will play a key role in shaping the architecture, quality, and visual polish of our customer-facing applications, web and mobile experiences.…
Added 4 months ago
T
QA Automation Engineer
Tubi
Toronto, Ontario
- Full-time
Tubi is seeking a highly skilled and experienced QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal…
Added 3 months ago
W
Principal Software Development Engineer - Applied AI
Wagepoint
Remote, Canada
- $200,000 to $220,000 CAD / year
- Full-time
- Remote
We’re looking for a talented Principal Software Development Engineer - Applied AI, who enjoys tackling hard problems and wants to create meaningful impact for small businesses across…
Added 3 months ago
CC
Senior Product Engineer - Onsite Position
Curtiss-Wright Corporation
Ottawa, ON · Canada-Ottawa
- Full-time
We’re seeking a passionate, Product Engineer who thrives on solving complex system-level challenges and is driven to push the boundaries of mission-critical embedded technology at our world…
Added 4 months ago
L
Senior Software Engineer (Back-end Focus)
LodgeLink
Calgary, Alberta
- Full-time
As a Senior Software Engineer, you should be comfortable around back-end coding languages, AI powered development frameworks, third-party libraries, and modern system design patterns such…
Added 4 months ago
TS
Automated Software Test Engineer
T-Rex Solutions
Remote, Canada
- $95,000 to $145,000 USD / year
- Full-time
- Remote
T-Rex Solutions is seeking an Automated Software Test Engineer to support the development of products using cutting edge technologies as part of a large modernization effort supporting the…
Added 3 months ago
E
Staff API Engineer
Equinix
Toronto, ON
- Full-time
Works with product teams, analysts, and other engineers to design and build systems and application software that enable a robust, usable API ecosystem. Implements and operates API…
Added 1 month ago
PC
Senior Automation Engineer - Toronto, ON (Hybrid)
Pozent Corporation
Toronto, ON
- Contract
Design, build, and maintain automated test frameworks and scripts independently to improve efficiency and test coverage, working in an Agile environment with business and T&D partner teams.
Added 1 month ago
SI
C++ Senior R&D Engineer
Synopsys Inc
Vancouver, BC
- Full-time
…from self-driving cars to learning machines. We lead in chip design, verification, and IP integration, empowering the creation of high-performance silicon chips and software content. Join…
Added 1 month ago
EA
Senior Software Engineer - Backend
Electronic Arts (EA)
Vancouver, BC
- Full-time
…contribute to our experiences, supported by thoughtful product design, safety systems, and global reach. Our focus is on enabling more players to participate in creative expression by…
Added 1 month ago
A
Mechanical Engineer
Actalent
Ottawa, ON
- Contract
This Mechanical Engineer role focuses on the design, development, and manufacturing of a torpedo launching system and related support equipment as part of a major naval defence program. You…
Added 4 months ago
EP
DevOps Administrator II
Engage People Inc.
Markham, Ontario
- Full-time
Provides subject matter expertise on the design and architecture of ongoing product evolutions.
Added 2 months ago
NF
Data Quality Engineer (Contract)
Northbridge Financial
Toronto, ON
- Full-time
- Contract
- Other
What is it like to be a Data Quality Engineer (Contract) at Northbridge Financial
Added 3 months ago
A
VP Nuclear Island - Monark
AtkinsRéalis
Mississauga, ON · Pickering, ON
- Full-time
Own the design delivery of the Nuclear Island scope on a large nuclear new‑build project, with accountability extending from scope definition through production of release for construction…
Added 2 months ago
Senior Platform Engineer - AI Platforms & Deployment - Landmark
Halliburton
Calgary, AB
You will design and maintain CI/CD pipelines, deployment automation, infrastructure-as-code, observability systems, and runtime environments that support both traditional enterprise…
Added 1 month ago
PI
Senior Software Engineer, Bet Engine
PENN Interactive
Canada
- Full-time
Design, scale, and performance-tune GraphQL APIs, low-latency gRPC services, and SQL queries powering the sportsbook wagering and grading engine, the casino transaction engine, the…
Added 4 months ago
A
NPI-LCE Test Engineer, Sr.
Adtran
Ottawa, Ontario
- Full-time
The NPI-LCE Test Engineer will be responsible for the development of automated test solutions for our photonic integration modules and assemblies. These test solutions will be used during…
Added 4 months ago
A
Staff Design Engineer, Canada
Ashby
Canada
- Full-time
This role truly expects you to design and code. Design Engineer at Ashby isn’t just a Frontend Engineer with new branding, nor is it a Designer vibe coding prototypes. Combining excellence…

Cerebras Systems

Staff Software Engineer, GPU Inference

Remote, Canada

Remote

Full-time

Apply About employer

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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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