About 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.

About the Role

As the Software Architect for Cerebras' manufacturing test platform, you will lead a team of Full Stack Engineers in designing and delivering the end-to-end software systems that power manufacturing test across every stage of our product lifecycle — from individual components to complete Cerebras systems. The platform spans both cloud infrastructure and physical client-server infrastructure deployed across our manufacturing facilities, and you will own the technical vision, architecture, and roadmap across the full stack. Working closely with hardware design, test engineering, operations, data analytics, and reliability teams, you will translate complex, cross-functional requirements into a cohesive software architecture that drives manufacturing efficiency, quality, and scale.

Responsibilities

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.
Lead, mentor, and grow a team of Full Stack Engineers, setting technical standards for code quality, design patterns, testing, documentation, and operational excellence.
Partner with hardware engineers, test developers, data engineers, operations, and reliability teams to translate business and engineering requirements into clear, scalable software designs.
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.
Conduct design and code reviews, guide technical trade-offs, and ensure the team is building secure, reliable, and maintainable systems.
Collaborate with engineering leadership on planning, prioritization, and delivery commitments, and represent the platform in cross-functional technical discussions.
Identify opportunities to improve manufacturing efficiency, quality, and scalability through better tooling, automation, data infrastructure, and platform capabilities.

Skills and Qualifications

Required

Bachelor's or Master's degree in computer science, computer engineering, or a related field.
8+ years of professional software engineering experience, including 2+ years in a technical leadership, staff engineer, or architect role.
Demonstrated experience designing and delivering complex, full-stack software systems at scale, including distributed systems and data-intensive applications.
Strong proficiency in at least one advanced programming language (e.g. Python, C++) and deep familiarity with modern full-stack development practices.
Experience architecting software for hardware manufacturing environments, such as manufacturing test automation, MES/test data systems, or manufacturing quality control.
Experience architecting and building client-server software, including designing the protocols, APIs, and deployment patterns that connect on-site infrastructure to broader platform services.
Experience with cloud platforms (e.g. AWS, GCP), including infrastructure-as-code, CI/CD, and production operations.
Experience designing systems backed by both SQL databases (e.g. PostgreSQL, MySQL) and NoSQL databases (e.g. MongoDB, Redis), including schema design, performance tuning, and data modeling.
Solid grounding in front-end technologies and frameworks (e.g. HTML, JavaScript, modern UI frameworks) and the ability to make sound architectural decisions about UI/API boundaries.
Track record of mentoring engineers, leading technical projects end-to-end, and partnering effectively with cross-functional stakeholders.

Preferred

Experience building distributed data platforms that synchronize across multiple sites or facilities.
Experience with data engineering, data analytics, and/or business intelligence platforms, and partnering with data teams on reporting and visualization.
Strong UI/UX sensibility and experience guiding the design of tools used by technical operators.
Experience with networking and cybersecurity considerations in industrial or manufacturing settings.

The base salary range for this position is $204,000 to $245,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.

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.

Read our blog: Five Reasons to Join Cerebras in 2026.

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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Skills & Tags

python java javascript go aws gcp machine learning ai

Aplyr's read

Cerebras Systems is at the forefront of AI hardware innovation, attracting top technical talent passionate about pushing the limits of high-performance computing.
Synthesized from recent postings & public sources

What's promising

•Cerebras Systems develops cutting-edge AI hardware, offering significant advancements in deep learning performance.
•The company's unique wafer-scale engine technology sets it apart in the semiconductor industry.
•Cerebras is expanding rapidly, creating diverse opportunities for engineers and technical staff.

What to watch

•The niche focus on AI hardware may limit broader market opportunities.
•High competition in AI hardware demands constant innovation to maintain leadership.
•Limited public information about financial stability and long-term viability.

Why Cerebras Systems

•Cerebras Systems' wafer-scale engine is the largest chip ever built, revolutionizing AI processing capabilities.
•The company focuses exclusively on AI and deep learning, offering specialized expertise.
•Cerebras' technology enables significantly faster AI model training compared to traditional hardware.

Aplyr’s read is generated by AI from public sources. Was it useful?

About Cerebras Systems

Cerebras Systems

cerebras.net

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Cerebras Systems is a technology company that specializes in developing high-performance computing solutions, particularly focused on artificial intelligence and deep learning applications.