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 openai.com 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 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: 1. Build a breakthrough AI platform beyond the constraints of the GPU. 2. Publish and open source their cutting-edge AI research. 3. Work on one of the fastest AI supercomputers in the world. 4. Enjoy job stability with startup vitality. 5. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here cerebras.ai! 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 cerebras.net to review our CCPA disclosure notice.

Requirements

Must-haves

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.
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

Nice-to-haves

Strong programming skills in Python and/or Go (experience with both is a plus).
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

Application prep

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Keywords to mirror

aici/cdkubernetespythongoml

Platform: ashby
Effort: quick