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Leads the design, scaling, and reliability of CoreWeave’s global observability stack—logging, tracing, and metrics—using tools like Prometheus, Grafana, and Kubernetes, while mentoring engineers and managing production clusters.
Leads architecture and performance for CoreWeave’s Kubernetes-native AI inference platform, optimizing GPU resource management and cost-per-token under strict SLAs.
Designs and leads CoreWeave’s Kubernetes-native orchestration platform for AI workloads, including SUNK, while setting long-term architecture and mentoring senior engineers.
Build and maintain scalable observability infrastructure for CoreWeave’s AI cloud platform, focusing on metrics, logging, tracing, and telemetry pipelines to support thousands of GPUs and petabyte-scale data.
Senior Software Engineer builds and maintains scalable observability infrastructure for AI cloud systems, focusing on metrics, logging, tracing, and telemetry pipelines in Kubernetes environments.
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading…
Designs and leads CoreWeave’s Kubernetes-native AI workload orchestration platform, optimizing scheduling and resource management for large-scale GPU clusters using tools like Kueue and Volcano.
Senior Site Reliability Engineer on CoreWeave's MetalDev team in Warsaw, splitting time (60/40) between production reliability work — incident response, on-call, SLOs — and building Go automation for bare-metal data centre infrastructure, using Kubernetes, Prometheus, and Grafana.
The hardware engineer will own GPU and PCIe health across CoreWeave’s high‑density GPU fleet in Warsaw, automating diagnostics, building monitoring/alerting, leading root‑cause analysis, and supporting on‑call and regional escalations. Core technologies include GPUs (H100+), NVIDIA interconnects, Python/Ansible, Redfish/IPMI, Prometheus, Grafana.
Design, build, and operate liquid‑cooling systems for high‑density GPU servers, automating hardware lifecycle, creating monitoring services, and handling thermal issue escalations across data‑centre facilities. Core technologies include Python/Ansible, Redfish/IPMI, and data‑centre thermal design.
Design, build, and maintain backend services, APIs, and libraries that automate OS provisioning and node software deployment for CoreWeave’s AI cloud, while handling on‑call support and production operations.
As a Site Reliability Engineer on CoreWeave's MetalDev team in Warsaw, you’ll split time between production operations (incident response, on‑call) and automation, writing Go code, building Prometheus/Grafana dashboards, creating self‑service tooling, and improving CI/CD pipelines for bare‑metal and Kubernetes infrastructure.
Build and maintain the MLOps platform that deploys, monitors, and scales AI workloads on CoreWeave’s high-performance cloud infrastructure.
The Staff Product Manager will own vision, strategy, and delivery for Physical AI products, focusing on data‑centre design tools that turn power budgets into rack‑and‑pod layouts using AI‑assisted prototyping and parametric optimization, while coordinating across engineering, research, and operations.
The Staff Product Manager will own vision, strategy and roadmap for CoreWeave’s Physical AI platform, collaborating with research, data science, engineering and enterprise customers to turn AI, robotics and cloud‑infrastructure technologies into scalable cloud products and integrations.
Builds and maintains a data-heavy web platform for AI engineering workflows using React, TypeScript, and Python, focusing on intuitive UIs for complex simulations and agent interactions.
Deploys AI solutions for engineering teams by applying machine learning to simulation, testing, and manufacturing data in customer environments.
Design and scale distributed data pipelines and MLOps infrastructure for a GPU-powered AI cloud platform, focusing on reliability, observability, and automated anomaly detection in a Kubernetes environment.
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