"gpu accelerated compute" Jobs
304 open tech roles matching “gpu accelerated compute”, taken straight from company career pages — not reposted from other job boards. Most in demand right now: Kubernetes, Python, Go. Every listing is re-checked daily and closed roles are removed.
Showing 20 of 304 results
Join Applied Intuition as an Embedded AI Engineer to develop on-device intelligence for Android Automotive platforms.
Lead the Execution Sandbox team at Databricks to architect and launch a new service for non-Spark compute workloads.
Join Clockwork Systems as a Senior Frontend Engineer to create powerful data visualizations in a fast-paced, inclusive environment.
Join Genesis Molecular AI as a Senior Infrastructure Engineer to enhance our multi-cloud compute infrastructure for drug discovery.
Join CoreWeave as Counsel, Global Supply Chain, providing strategic legal support for procurement and logistics in a fast-paced environment.
Join IonQ as a Senior HPC Cluster Engineer to design and maintain high-performance computing systems for quantum simulations.
Lead complex cross-functional programs in performance and benchmarking for CoreWeave's AI/ML Platform Services.
Join Clockwork Systems as a Software Development Engineer in Test to enhance testing and CI/CD infrastructure in a fast-paced startup environment.
Drive the adoption of CoreWeave's data services by identifying market opportunities and shaping product strategy for enterprise customers.
Lead and scale CoreWeave's Platform Security engineering function, focusing on security in Kubernetes and multi-cloud environments.
Lead the development of a hybrid quantum-classical computing platform at IonQ, integrating quantum and classical workloads.
Join CoreWeave as a Senior Engineer to enhance Kubernetes-native benchmarking services and improve performance across a global infrastructure.
Lead the verification strategy for Graphcore's AI accelerators, driving high-quality silicon delivery in a global team.
Lead the engineering organization at Inferact to develop systems for vLLM, focusing on GPU performance and ML systems optimization.
Join Anthropic as a Performance Engineer to optimize AI inference systems for throughput, latency, reliability, and correctness.