Senior Inference Platform SDET

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.

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

• 5+ 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).
• 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).
• Familiarity with performance debugging, profiling, or system observability tools.
• Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.