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Cerebras

Senior SDET, Inference Platform

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 7, 2026
Experience: 3+ years of experience in software engineering, QA/quality engineering, systems engineering, or infrastructure development.
Posting language: English
Posted: Sep 23, 2026

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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

We are looking for an Inference Platform SDET to join the Inference Service Quality team at Cerebras and work on the inference platform. This team sits at the intersection of distributed systems, cloud and cluster infrastructure, and the software stack that serves the world's fastest AI inference.

In this role, you will own the quality and reliability of the infrastructure that deploys and runs the Cerebras Inference Platform - from CI/CD pipelines and Kubernetes-based deployments to ingress, load balancing, and service discovery. You will validate the platform both in cloud environments and on real Cerebras clusters, working side by side with the Inference Platform development team to catch issues before our customers do.

This is an excellent opportunity for engineers who enjoy infrastructure, automation, and debugging across the full deployment stack, and who want to ensure that a platform serving inference at massive scale stays fast, reliable, and production-ready.

Responsibilities

Design, build, and maintain test infrastructure and automation for deploying and validating the Cerebras Inference Platform.
Validate the platform across environments - from cloud-managed Kubernetes to deployments running on Cerebras hardware.
Test and verify deployment infrastructure including Kubernetes workloads, CI/CD pipelines, ingress and service discovery, NGINX, and load balancing.
Collaborate closely with the Inference Platform development team to ensure new features and platform capabilities ship reliably.
Investigate and debug complex issues spanning networking, orchestration, deployment, and distributed services.
Develop and maintain testbeds used to validate platform performance, scalability, and reliability.
Identify failure points, bottlenecks, and edge cases that impact platform stability and inference performance.
Contribute to test plans and validation strategies for new platform features and releases.
Improve observability, diagnostics, and debugging workflows across the inference platform stack.
Partner with engineering teams to ensure high-quality, production-ready releases of the Cerebras Inference Platform.

Minimum Skills & Qualifications

3+ years of experience in software engineering, QA/quality engineering, systems engineering, or infrastructure development.
Strong programming skills in Python and/or Go (experience with both is a plus).
Experience building automation tools, testing frameworks, or internal developer tooling.
Hands-on experience with CI/CD systems (e.g., Jenkins)
Experience debugging complex systems, distributed services, or networked infrastructure.
Familiarity with systems-level development, infrastructure tooling, or platform integration.
Strong problem-solving skills and the ability to investigate issues across multiple system and infrastructure layers.
Excellent communication and collaboration skills.
Experience mentoring junior engineers

Preferred Skills

Hands-on experience with Kubernetes and container orchestration in a real production or staging environment.
Experience with cloud-managed Kubernetes such as Amazon EKS.
Experience with GitOps/deployment tooling (e.g., ArgoCD).
Familiarity with ingress controllers, service discovery, NGINX, and load balancing.
Experience with build systems such as Bazel.
Experience with cluster tooling and operations (e.g., k9s).
Exposure to performance debugging, profiling, or system observability tools.
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads

Location: Toronto / Sunnyvale

Team: Inference Service Quality

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

Build and maintain automated test infrastructure to validate the Inference Platform across cloud-managed Kubernetes environments and Cerebras hardware, including deployments, CI/CD, networking, ingress, and load balancing. Investigate cross-stack issues, maintain testbeds for performance and reliability validation, improve observability and debugging, and collaborate with development teams to deliver production-ready releases.

Requirements

Candidates need at least three years of experience in software engineering, quality engineering, systems engineering, or infrastructure development, along with strong Python and/or Go skills and experience building automation or testing tools. They should be able to debug distributed systems and networked infrastructure, work with CI/CD systems, and communicate and collaborate effectively; Kubernetes, EKS, GitOps, and inference infrastructure experience are preferred.

Skills

Python
Go
Test Automation
Testing Frameworks
CI/CD
Kubernetes
Amazon EKS
ArgoCD
NGINX
Ingress Controllers
Service Discovery
Load Balancing
Distributed Systems Debugging
Bazel
Cluster Operations
Performance Debugging

Visa sponsorship

Not detected in the job text

Keywords

Inference Platform
Test Infrastructure
Test Automation
Python
Go
CI/CD
Jenkins
Kubernetes
Amazon EKS
ArgoCD
GitOps
NGINX
Ingress Controllers
Service Discovery
Load Balancing
Distributed Systems
Cloud Infrastructure
Cluster Infrastructure
Cerebras Hardware
Bazel
k9s
Performance Testing
Scalability
Reliability
Observability
Model Serving
ML Inference
GPU-Accelerated Workloads
Networking

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