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.
- 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.
- 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.
- 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.
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.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
Skills Required
- Bachelor's or Master's degree in computer science, computer engineering, or related field
- 8+ years of professional software engineering experience
- 2+ years in a technical leadership, staff engineer, or architect role
- Experience designing and delivering complex, full-stack software systems
- Strong proficiency in at least one advanced programming language (e.g. Python, C+)
- Experience architecting software for hardware manufacturing environments
- Experience architecting and building client-server software systems
- Experience with cloud platforms (e.g. AWS, GCP)
- Experience designing systems backed by both SQL and NoSQL databases
- Grounding in front-end technologies and frameworks
- Track record of mentoring engineers and leading technical projects
Cerebras Systems Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cerebras Systems and has not been reviewed or approved by Cerebras Systems.
-
Fair & Transparent Compensation — Pay is considered competitive for an AI‑hardware firm, and many employees are described as generally happy with compensation. Sentiment indicates compensation is viewed favorably while acknowledging variation by role and seniority.
-
Healthcare Strength — Health coverage is described as top quality with medical, dental, and vision included. Premiums are reportedly fully covered for employees in some plans, increasing perceived value.
-
Flexible Benefits — Work‑from‑home flexibility is regarded as strong. Flexible arrangements complement standard offerings like vacation, sick leave, and paid holidays.
Cerebras Systems Insights
What We Do
Cerebras Systems is a team of pioneering computer architects, computer scientists, deep learning researchers, functional business experts and engineers of all types. We have come together to build a new class of computer to accelerate artificial intelligence work by three orders of magnitude beyond the current state of the art. The CS-2 is the fastest AI computer in existence. It contains a collection of industry firsts, including the Cerebras Wafer Scale Engine (WSE-2). The WSE-2 is the largest chip ever built. It contains 2.6 trillion transistors and covers more than 46,225 square millimeters of silicon. The largest graphics processor on the market has 54 billion transistors and covers 815 square millimeters. In artificial intelligence work, large chips process information more quickly producing answers in less time. As a result, neural networks that in the past took months to train, can now train in minutes on the Cerebras CS-2 powered by the WSE-2. Join us: https://cerebras.net/careers/
.png)
