Key technologies and capabilities for this role
Common questions about this position
The position is hybrid.
This information is not specified in the job description.
The role requires expertise in designing and managing large-scale GPU cluster environments, developing scheduling and orchestration strategies like Kubernetes and Slurm for AI/ML workloads, and driving architecture decisions for high-throughput networking, low-latency storage, and resource scheduling.
CoreWeave thrives in a dynamic environment where adaptability and resilience are key, offering career-defining opportunities for those who excel amid change and challenge, solve complex problems, and make significant impact.
Strong candidates thrive in dynamic environments, enjoy solving complex problems, excel amid change and challenge, and have the ability to lead high-performance teams while defining AI compute strategies.
Cloud service for GPU-accelerated workloads
CoreWeave provides cloud computing services that focus on GPU-accelerated workloads, which are essential for tasks requiring high computational power. Their services cater to industries such as artificial intelligence, machine learning, visual effects rendering, and data processing. Clients can access powerful computing resources on a pay-as-you-go basis, allowing them to avoid the costs of purchasing expensive hardware. CoreWeave's infrastructure utilizes a bare metal serverless Kubernetes platform, which enhances performance while minimizing operational complexity for users. This setup enables clients to optimize their computing needs with a variety of NVIDIA GPUs, ensuring they can balance performance and cost effectively. The company's goal is to offer flexible and scalable computing solutions that meet the demands of diverse clients, from tech companies to film studios.