Senior SDET, Inference Platform
Cerebras is hiring a Senior SDET, Inference Platform for a remote role open to applicants in United States. Level rates it ; you can apply on Cerebras.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- This is listed as a remote role.
- The posting mentions OpenAI, Kubernetes and Nginx among its tools and skills.
- Level classes it as a senior role.
- Cerebras has 121 other open roles on Level.
AI in this role
Owns the test infrastructure and quality of a high-speed AI inference platform running on specialized hardware.
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
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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How we rate this
Senior SDET, Inference Platform at Cerebras rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where testing was part of your work. What did you do?
- Tell me about a project where automation was part of your work. What did you do?
- Tell me about a project where qa was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Research, Testing, Automation, Qa, and Infrastructure. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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