Cerebras powers the world's fastest AI inference on the biggest wafer chip. Cerebras CS-4 delivers up to 30x faster inference than GPUs.
About the role
We are hiring a Software Engineer to design and build the core software behind Cerebras engineering infrastructure. You will work on Python frameworks, orchestration systems, distributed execution, scheduling, test infrastructure, and developer tooling. You will help define the architecture and APIs that other engineering teams depend on every day.
What they're looking for
- 3+ years of professional software-engineering experience
- Strong proficiency in Python and a solid understanding of the language’s strengths, limitations, and runtime behavior
- Experience designing maintainable software systems, libraries, frameworks, backend services, or developer-facing APIs
- Good judgment around software architecture, abstraction boundaries, design patterns, extensibility, and long-term maintainability
- Understanding of concurrency concepts such as processes, threads, asynchronous execution, synchronization, and shared state
- Foundational understanding of operating systems, including processes, signals, filesystems, resource management, and program execution
More about this role
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; 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.
Cerebras works with the leading 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.
The Core Infrastructure team builds the software systems that power engineering workflows across Cerebras.
Our infrastructure coordinates complex work across machines, clusters, development environments, and hardware systems. We build orchestration frameworks, execution engines, scheduling systems, test infrastructure, developer tools, and reusable software platforms that allow engineers to build, test, qualify, and deliver software reliably at scale.
These systems are primarily built in Python,...
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