Cerebras powers the world's fastest AI inference on the biggest wafer chip. Cerebras CS-4 delivers up to 30x faster inference than GPUs.
About the role
We are looking for a hands-on SDET Technical Lead to establish and lead Release Integration Testing within Release & Feature Qualification for AI Inference Core. The Production Engine for Inference Core — turning integrated features into reliable production releases.
What they're looking for
- Strong software-engineering fundamentals and programming ability in Python Go, or a similar language
- Demonstrated technical leadership in software quality, test infrastructure, systems validation, release engineering, or complex software integration
- Experience designing automation and test architecture for distributed, systems-level, infrastructure, or AI software
- Proven ability to break down ambiguous cross-stack failures, form hypotheses, gather evidence, and drive issues to resolution
- Strong understanding of risk-based testing, release readiness, regression strategy, failure analysis, and quality metrics
- Ability to influence and align multiple engineering teams without relying solely on organizational authority
More about this role
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.
We are looking for a hands-on SDET Technical Lead to establish and lead Release Integration Testing within Release & Feature Qualification for AI Inference Core.
The Production Engine for Inference Core — turning integrated features into reliable production releases.
You will define the quality strategy across the pre-release and release cycle, from feature and model integration through branch stability, release qualification, deployment, and post-release learning. You will work across AI...
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