AI Inference Core - Senior SDET, Release Integration Testing

The role

You will develop automated test frameworks and validate complex AI inference systems. You will investigate cross-stack failures and drive improvements in release quality and reliability across AI frameworks, runtime, compiler, kernels, and hardware.

What you will do

• Design, develop, and maintain automated test frameworks, tools, and infrastructure.
• Own integration testing and qualification activities for complex inference-core features.
• Develop and execute end-to-end, integration, regression, and system-level tests.
• Analyze test results to assess readiness and provide recommendations for release qualification.
• Investigate and debug complex cross-stack failures and perform root cause analysis.
• Improve master and release-branch stability by identifying regressions and triaging failures.
• Build and enhance internal tooling for test automation, diagnostics, and CI/CD workflows.
• Collaborate with feature engineering, infrastructure, and release teams.
• Contribute to test architecture and risk-based testing strategies.
• Provide technical guidance and mentorship to junior engineers.

Required qualifications

• Professional experience developing software, automated testing frameworks, or test infrastructure.
• Proficiency in Python, Go, or a similar programming language.
• Experience designing, developing, and maintaining automated tests and frameworks for complex software systems.
• Strong debugging and problem-solving skills to investigate failures across multiple components.
• Solid understanding of software testing methodologies including integration, system, regression, and end-to-end validation.
• Experience working with CI/CD pipelines, test automation infrastructure, and software development workflows.
• Working knowledge of operating systems, networking, distributed systems, or systems-level software concepts.
• Ability to independently own complex technical problems and drive issues through resolution.
• Strong communication and collaboration skills.

Nice to have

• Experience testing or developing distributed systems, infrastructure software, runtime systems, compilers, kernels, or other low-level software.
• Experience with AI/ML infrastructure, LLM inference, model deployment, multimodal workloads, or large-scale compute environments.
• Exposure to hardware accelerators, GPU systems, software/hardware integration, or high-performance computing.
• Experience building scalable test frameworks, distributed test systems, release pipelines, or internal developer tools.
• Familiarity with performance testing, profiling, observability, fault injection, reliability engineering, or production failure analysis.
• Experience with containers, Kubernetes, cloud infrastructure, cluster orchestration, or large-scale distributed computing environments.
• Experience using debugging and observability tools to diagnose complex system-level issues.
• Experience working in fast-paced engineering environments, including startups or teams developing complex systems software.

Benefits

• Build a breakthrough AI platform beyond the constraints of the GPU.
• Publish and open source cutting-edge AI research.
• Work on one of the fastest AI supercomputers in the world.
• Job stability with startup vitality.
• Simple, non-corporate work culture that respects individual beliefs.

About the company

Cerebras Systems builds the world's largest AI chip. The company works with leading model labs, global enterprises, and cutting-edge AI-native startups.