Lead Full Stack Machine Learning Engineer

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.

This teams' principal responsibility is to rapidly bring up state-of-the-art open-source models, frameworks and data engineering. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire software stack. Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications.

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  Contribute to the end-to-end bring up of frameworks for RL, inference serving, ML models on Cerebras CSX systems.

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  Work across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning.

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  Debug performance and correctness issues spanning model code, compiler IRs, runtime behavior, and hardware utilization.

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  Propose and prototype improvements across tools, APIs, or automation flows to accelerate future bring ups.

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field with 10+ years’ experience.

• Comfort navigating the full AI toolchain: Python modelling code, compiler IRs, performance profiling, etc.

• Strong debugging skills across performance, numerical accuracy, and runtime integration.

• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with model internals (e.g., attention, MoE, diffusion).

• Proficiency in C/C++ programming and experience with low-level optimization.

• Strong background in optimization techniques, particularly those involving NP-hard problems.

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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