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Added 1 month ago
ES
AI practice lead - Financial services and Insurance
EPAM Systems
Canada
- Full-time
Added 1 month ago
C
Senior Software Engineer - AI / ML
CyberCoders
Canada
- Full-time
We're looking for a Senior AI/ML Engineer to help expand our next-generation document intelligence system. Working in close collaboration with our Data Science team, you'll bring deep…
Added 5 months ago
E
Digital - ASIC Design Automation Engineer
Eliyan
Toronto, Ontario
- Full-time
Added 1 month ago
KD
AI/ML Engineer
Katalyst Data Management
Calgary, AB
- Full-time
Join the dynamic and collaborative team at Katalyst Data Management (KDM)! KDM is seeking an AI/ML Engineer to support the operation, optimization, and reliability of the infrastructure…
Added 1 month ago
Senior AI/ML Engineer
Katalyst Data Management
Calgary, AB
Join the dynamic and collaborative team at Katalyst Data Management (KDM)! KDM is seeking a Senior AI/ML Engineer to help design, build, and operate the infrastructure that powers our next…
Added 1 month ago
CS
Distributed Software Engineer
Cerebras Systems
Remote, Canada
- Full-time
- Remote
Added 1 month ago
P
Senior Full Stack Engineer
Procurify
Remote, Canada
- $122,000 to $152,000 CAD / year
- Full-time
- Remote
Added 1 month ago
AG
Senior AI Developer / Développeur(se) IA senior
Aduna Global
Montreal, QC
- Full-time
Production first. Every engineer is close to what runs and to the customers who use it.
Added 1 month ago
AG
DevSecOps – MTL / DevSecOps – Montréal
Aduna Global
Montreal, QC
- Full-time
…engineering to move fast and adopt AI safely. As a Senior Security Engineer, you'll be an individual contributor accountable for implementing security solutions across Aduna's platform and…
Added 1 month ago
M
AI Engineer, Innovation
MNP
AB
- Full-time
Make an impact with our Technology - Development team as an AI Engineer, Innovation. This diverse team of tech-savvy builders and problem solvers embraces digital transformation, and the…
Added 1 month ago
K
Machine Learning Data Engineer
kadence
Montreal, QC
- Full-time
Added 1 month ago
X
AI Specialist - AI For Research
Xanadu
Toronto, ON
- Full-time
4+ years of ML/Research Engineer experience developing models and/or AI tools in a scientific/engineering research environment.
Added 1 month ago
CI
Lead Software Engineer, AI & Emerging Tech
CPP Investments | Investissements RPC
Toronto, ON
- Full-time
As a Lead Engineer for AI & Emerging Tech, you will drive AI platform enablement across the enterprise, you will drive the design, development, and deployment of next-generation tech and…
Added 1 month ago
FC
Portfolio Engineer
Fidelity Canada
Toronto, ON
- Full-time
The Managed Accounts Portfolio Engineer (“the engineer”) will be responsible for delivering repeatable portfolio construction and oversight capabilities. They will do this by building and…
Added 1 month ago
A
Senior Software Engineer, Inference
AssemblyAI
Toronto, ON
- $190,000 to $225,000 USD / year
- Full-time
We're hiring a Software Engineer to help turn cutting-edge AI research into products our customers rely on every day. You'll sit on a fast-paced engineering team between our research org…
Added 1 month ago
Sr. AI Engineer (AI/ML Inference)
Dialpad
Vancouver, BC
As a Sr. AI Engineer: Systems, you’ll serve as an embedded senior back-end engineer on our Speech Team, owning the production systems that turn speech models and third-party capabilities…
Added 1 month ago
E
Senior Product Manager
EviSmart™
Vancouver, BC
- Full-time
You have been accountable for whether code ships. You were an engineer before you were a PM, or you've had engineers report to you, or you still write code as part of your job.
Added 1 month ago
GD
Co-op Winter 2027 – Project Engineer - 8 to 12 months
General Dynamics Missions System International
Ottawa, ON
- Internship
General Dynamics Mission Systems - Canada has a requirement for a Junior Project Engineer to join the International TacCIS group. The successful candidate will be expected to work alongside…
Added 1 month ago
AL
Senior Full-Stack Software Engineer
Altis Labs
Remote, Canada
- Full-time
- Remote
Altis Labs is recruiting a Senior Full-Stack Software Engineer with an entrepreneurial, product-focused mindset. You'll design and implement testable, scalable code as we expand our…
Added 2 months ago
FR
Lead Machine Learning Engineer - AI Innovation Teams
Fitch Ratings
Toronto, ON
- Full-time
Lead Machine Learning Engineer – AI Innovation Teams
Added 1 month ago
F
Senior Data Engineer / Ingénieur(e) de données senior
Flinks
Remote, Canada
- Full-time
- Remote
We're hiring our Senior Data Engineer (Data / ML Platform) to stand up data engineering as a discipline at Flinks. You'll own the data and ML platform that turns models into reliable…
Added 1 month ago
P
Senior Full Stack Engineer
Procurify
Remote, Canada
- Full-time
- Remote
Added 1 month ago
Q
Firmware Engineer – SerDes PHY (all levels)
Qualcomm
Toronto, ON
- Full-time
…a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or…
Added 1 month ago
WT
Senior Java Software Engineer
Wissen Technology
Montreal, QC
- Full-time
Added 1 month ago
C
Senior Software Engineer, GPU Infrastructure (HPC)
Cohere
Remote, Canada
- Full-time
- Remote

Cerebras Systems

Distributed Software Engineer

Remote, Canada

Remote

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Workplace: Remote
Posting language: English
Posted: Sep 8, 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.

The Role

The Cluster engineering team owns the software that turns thousands of wafers, servers, and switches into a cloud that stays up, stays busy, and stays debuggable. We stand clusters up from bare metal, schedule training and inference workloads across the fleet, keep it healthy, and make it observable to users, operators, and increasingly to AI agents. The stack is Go and Python on Kubernetes, running both on-premise deployments and our own cloud.

Responsibilities

· Declarative, CRD-driven automation of bare-metal networking, OS, and application software across clusters of Cerebras systems, servers, and switches, built to reconcile thousands of nodes

· Push-button cluster install, upgrade, and security patching with real downtime budgets, gated by canaries

· Kubernetes operators that schedule large inference workload: resource locks, priority queues, network topology, and health-aware placement

· gRPC control-plane services, authorization, admission webhooks, and quota policy for a multi-tenant fleet

· Metrics and log pipelines with purpose-built exporters for wafer-scale systems, servers (Redfish, IPMI), and network fabric (gNMI, sFlow), on Prometheus and Grafana, with SLOs and alerting

· Failure detection, HA control planes, and automated recovery, plus the CLIs, APIs, and MCP gateway that expose the fleet to users, operators, and AI agents

Skills and Qualifications

· 5+ years building and operating production distributed systems or infrastructure software

· Production-quality Go and Python

· Real Kubernetes depth: you have written or debugged controllers and operators, and you understand CRDs, reconciliation semantics, informer caches, admission webhooks, and RBAC

· Strong debugging skills across distributed systems, Linux, and networking

· Prometheus and Grafana as a practitioner: PromQL, exporter design, cardinality discipline, useful alerts

· Strong self-driving capability. This environment is large, fast-moving, and not fully documented, so we need engineers who build their own context, decide, and drive work across team boundaries. Learning speed matters more here than familiarity with our stack.

· Demonstrated adoption of AI in your engineering workflow: active use of coding agents, a view on where they help and where they mislead, and the rigor to verify what they produce.

· Nice to have: bare-metal or HPC fleet operations, scheduler internals, RDMA/RoCE and eBPF networking, Ceph or NVMe-oF, etcd and HA upgrades, inference serving stacks. ML research experience is not required.

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 be responsible for building and maintaining the software infrastructure that manages large-scale clusters of servers and switches. This includes developing Kubernetes operators, automating bare-metal networking, and ensuring the health and observability of the fleet.

Requirements

Candidates must have at least 5 years of experience in building production-grade distributed systems or infrastructure software. Proficiency in Go and Python, along with deep expertise in Kubernetes and distributed system debugging, is essential.

Skills

Go
Python
Kubernetes
Distributed systems
Infrastructure software
CRDs
Prometheus
Grafana
gRPC
Linux
Networking
Bare-metal automation
Failure detection
API development
Cloud infrastructure

Visa sponsorship

Not detected in the job text

Keywords

Distributed Systems
Go
Python
Kubernetes
CRD
Bare-metal
Networking
gRPC
Prometheus
Grafana
Cloud
Automation
HPC
RDMA
RoCE
eBPF
Ceph
NVMe-oF
etcd
Inference
AI
Infrastructure
Linux
Redfish
IPMI
sFlow
gNMI
Admission Webhooks
RBAC
Observability

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