CPU Jobs
3 open roles mentioning CPU
Senior Software Engineer, Model Serving
Databricks
Databricks' Model Serving product offers enterprises a unified, scalable, and governed platform for deploying and managing AI/ML models, including traditional ML and large language models. It provides real-time, low-latency inference, governance, monitoring, and lineage, making it a core pillar for customers operationalizing models at scale with strong SLAs and cost efficiency. As a Senior Engineer, you will be instrumental in shaping both the product experience and the foundational infrastructure of Model Serving. You will design and build high-throughput, low-latency inference systems for CPU and GPU workloads, influence architectural direction, and collaborate with cross-functional teams to deliver a world-class serving platform.
$166k - $225k
Senior ASIC RTL Design Engineer, AI Hardware
Cerebras
Cerebras Systems is seeking a senior front-end design engineer to join the world-class team designing and developing the next generations of the Cerebras Wafer Scale Engine (WSE). This role involves deep expertise in RTL design and integration, focusing on high-performance, power-efficient, and scalable solutions. You will collaborate closely with verification, physical design, software, and system teams to bring innovative semiconductor architectures from concept to production, tackling the unique challenges of building WSE systems. The company's architecture enables industry-leading AI training and inference speeds, transforming AI applications and unlocking real-time iteration and agentic computation.
$200k - $290k
ML Algorithm Mapping and Performance Engineer, Core ML
Cerebras
The Core ML team is seeking an engineer to map novel algorithms for efficient large-scale AI training and inference to the Cerebras architecture. This role involves determining when these algorithms outperform competing approaches and how their advantages scale with models, workloads, and hardware. 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, influencing research directions, implementation on current systems, and future hardware/software capabilities.