Cerebras

Mid-sized

Cerebras Systems is an American semiconductor company that designs large-scale AI processors, most notably its Wafer-Scale Engine, one of the largest computer chips ever built. It provides hardware and cloud-based systems optimized for training and running large AI and deep learning models.

3 interview notes · updated Jul 2026

Cerebras·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026

Behavioral-ish interview for a software engineer role at Cerebras. Three questions, all pretty open-ended, leaning more on how you think and handle people than on technical chops.

When you're working in an area with little documentation or structured information, how do you go about learning it effectively?
Tell me about a significant conflict you had with a manager or someone more senior. How did you handle it?
How do you generally approach learning something new?

“This one tripped me up a bit because I kept wanting to give a generic answer about reading docs.”

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Cerebras·Software Engineer·Technical Phone Screen

May 2026

Cerebras software engineer interview with a meaty systems question that covered dense vector ops, parallel optimization, and sparse vector handling all in one shot. The kind of question where you think you're done after part one and then they keep going.

Implement a dot product for two dense vectors, then walk through how you'd optimize it for a parallel architecture (SIMD, multithreading, memory alignment, cache behavior), and finally explain how you'd handle the same operation when the vectors are sparse, including data structures, complexity changes, and how sparsity complicates parallelization.

“Three questions dressed up as one.”

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Cerebras·Software Engineer·Onsite - System Design / Architecture

May 2026

System design round at Cerebras for a software engineering role, focused almost entirely on a custom message queue with some pretty specific constraints around multi-channel routing and subscription logic. Not your typical LRU cache warmup.

Design a message queue data structure that supports attaching multiple communication channels to a single message, and allows consumers to subscribe to specific channels.
How would you extend the design to support adding new channels dynamically, and how do you figure out the minimum number of channels needed to cover a given set of producer-consumer communication patterns?
How would you represent channel identifiers so that you can use union and intersection operations to efficiently detect which channels are shared between messages or subscribers?
Walk through the time and space complexity of enqueue, dequeue, subscribe, unsubscribe, and channel-query operations in your design.

“I started with a pretty standard queue backed by a list and then had to layer on the channel stuff, which is where it got messy.”

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