Senior HPC Engineer, GPU Compute

Nebius · Berlinsenior

En corto

▸Ingeniero Senior en HPC enfocado en optimizar clusters GPU e InfiniBand en una plataforma cloud de IA.
▸Día a día: depurar problemas de rendimiento, integrar hardware nuevo, automatizar monitoreo y mejorar sistemas virtuales con KVM/QEMU.
▸Destacado: trabajo directo con tecnologías de punta como InfiniBand y virtualización de GPU en entornos HPC a escala hyperscaler.

Fluency in English required for technical collaboration.

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¿Qué piden?

✓5+ años en desarrollo de software a nivel de sistema con enfoque en optimización de rendimiento.
✓3+ años de experiencia práctica con sistemas Linux (administración, resolución de fallos, tuning).
✓Conocimiento profundo de arquitectura de servidores, PCIe, NICs, kernel Linux y sistemas HPC.
✓Dominio de lenguajes de alto rendimiento: C/C++, Go o Python.
✓Experiencia con virtualización KVM/QEMU y emulación de dispositivos.
✓Capacidad para analizar y resolver problemas en entornos de GPU y redes InfiniBand a gran escala.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

LinuxKVMQEMUKubernetesC/C++GoPythonRDMARoCEInfiniBand

¿A quién escribirle en Nebius?

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About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role We’re looking for a Senior HPC Cluster Engineer to join our team and play a key role in the development of our cutting-edge hyperscaler platform. The GPU & InfiniBand team is responsible for enhancing and optimizing the core components of our Cloud platform, with a specific focus on GPU computing, InfiniBand networks, and the KVM/QEMU stack. You’ll work closely with hardware virtualization and device emulation technologies, ensuring high performance and security in multi-GPU, HPC environments. The role involves analyzing, troubleshooting, and improving infrastructure to support new hardware, fine-tuning system performance, and automating fault detection and resolution in a complex system. In this position, you will be responsible for: • Tuning the performance of GPU clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments. • Analyzing and troubleshooting the root cause of issues related to GPUs and InfiniBand networks, and proposing corrective actions. • Integrating new hardware into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM. • Enhancing automation systems for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments. • Configuring and managing GPU devices and InfiniBand fabrics, ensuring efficient and reliable operation. We expect you to have: • 5+ years of professional experience in system-level software development (focused on performance optimization, low-level programming). • 3+ years of hands-on experience with Linux systems (administration, troubleshooting, and performance tuning). • In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems. • Strong proficiency in one or more performance-oriented programming languages (C/C++, Go, Python). It would be a plus if you have: • Experience with GPU end-to-end testing in a cluster environment using InfiniBand networking. • Proven track record of analyzing and optimizing the performance of HPC workloads (e.g., simulations, data analysis, AI/ML workloads). • Familiarity with RDMA, RoCE, and InfiniBand protocols for high-performance communication. • Background in Software-Defined Networking (SDN) and experience with HPC cluster networking . • Understanding of QEMU/KVM virtualization and ma

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