Software Architect – Manufacturing Test
Cerebras SystemsAbout the role
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include top 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.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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.
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Define and own the technical architecture and long-term roadmap for the manufacturing test software platform, including test execution frameworks, user interfaces, distributed data storage, cloud services, on-site client-server systems, and reporting.
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Lead, mentor, and grow a team of Full Stack Engineers, setting technical standards for code quality, design patterns, testing, documentation, and operational excellence.
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Partner with hardware engineers, test developers, data engineers, operations, and reliability teams to translate business and engineering requirements into clear, scalable software designs.
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Drive key architectural decisions across the stack — from front-end frameworks and API design to database schemas, distributed data synchronization, cloud deployments, and on-prem infrastructure across multiple manufacturing facilities.
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Conduct design and code reviews, guide technical trade-offs, and ensure the team is building secure, reliable, and maintainable systems.
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Collaborate with engineering leadership on planning, prioritization, and delivery commitments, and represent the platform in cross-functional technical discussions.
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Identify opportunities to improve manufacturing efficiency, quality, and scalability through better tooling, automation, data infrastructure, and platform capabilities.
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Bachelor's or Master's degree in computer science, computer engineering, or a related field.
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8+ years of professional software engineering experience, including 2+ years in a technical leadership, staff engineer, or architect role.
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Demonstrated experience designing and delivering complex, full-stack software systems at scale, including distributed systems and data-intensive applications.
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Strong proficiency in at least one advanced programming language (e.g. Python, C++) and deep familiarity with modern full-stack development practices.
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Experience architecting software for hardware manufacturing environments, such as manufacturing test automation, MES/test data systems, or manufacturing quality control.
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Experience architecting and building client-server software, including designing the protocols, APIs, and deployment patterns that connect on-site infrastructure to broader platform services.
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Experience with cloud platforms (e.g. AWS, GCP), including infrastructure-as-code, CI/CD, and production operations.
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Experience designing systems backed by both S
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