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 global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.
About the team
The Inference Ecosystem Engineering team’s mission is to show—not tell—the power of the Cerebras Inference API. We build open-source integrations, reference architectures, and polished demo apps that developers can clone, run, and extend in minutes. From LangChain agents to partner plug-ins and end-to-end “weekend projects,” our code is often the first (and most lasting) impression customers have of Cerebras.
Responsibilities:
- Design, develop, and maintain open-source libraries, SDKs, and sample repos that make Cerebras the easiest-to-adopt inference platform.
- Create production-quality demo applications that highlight low latency, high gen speed, and cost advantages.
- Build and own CI/CD pipelines, tests, and release automation for all public repos.
- Collaborate with partner engineering teams to embed Cerebras inference into their products and publish joint reference architectures.
- Collect developer feedback, identify usability gaps, and influence the Cerebras API roadmap.
- Contribute to engineering blogs, tutorials, and conference talks to grow community awareness and adoption.
Skills & Qualifications:
- Bachelor’s or Master's degree in computer science or related field, or equivalent practical experience.
- 4+ years professional software engineering experience (or equivalent open-source track record).
- Solid understanding of GenAI applications and design patterns such as RAG.
- Proficiency in Python and/or TypeScript/JavaScript
- Hands-on with at least one modern LLM framework (LangChain, LlamaIndex, CrewAI, AutoGen, etc.).
- Multiple non-trivial open-source contributions, preferably to GenAI projects
- Ability to move quickly from whiteboard idea to working prototype; bias toward shipping polished developer experiences.
- Strong communication skills—you enjoy writing clear docs and telling a compelling technical story.
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 2025.
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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Top Skills
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/
