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.
Requirements
- 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.
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.
Other
- Bachelor’s or Master’s degree in computer science or related field, or equivalent practical experience.
- 2+ years professional software engineering experience (or equivalent open-source track record).
- Strong communication skills—you enjoy writing clear docs and telling a compelling technical story.
