ML Algorithm Mapping and Performance Engineer, Core ML

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 ML team develops novel algorithms for efficient large-scale training and inference. We are looking for an engineer who can determine how these algorithms should be mapped to the Cerebras architecture, when they outperform competing approaches, and how their advantages change as models, workloads, and hardware systems scale.

You will combine analytical performance modeling, empirical benchmarking, and hands-on prototyping to characterize the efficiency frontiers of emerging ML algorithms. Your work will span kernel-level and end-to-end performance, helping the team reason about trade-offs among model quality, latency, throughput, memory, communication, and compute utilization.

This role will directly influence which research ideas Core ML pursues, how those ideas are implemented on current Cerebras systems, and which capabilities should be considered in future generations of hardware and software.

…