About the Job
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.
Key Responsibilities
The role involves forming technical hypotheses, designing targeted tests, analyzing system logs and low-level hardware data, and distinguishing between GPU, host, firmware, interconnect, thermal, and physical hardware failures. It requires strong ownership, curiosity, and the ability to turn ambiguous problems into evidence-based conclusions and repeatable troubleshooting procedures.
This is a senior systems engineering role focused on diagnosing and resolving complex hardware and platform failures in high-performance AI infrastructure. This engineer will work across Linux, GPU servers, PCIe, firmware, power, and cooling to determine the true root cause of issues that may not have an existing troubleshooting procedure.
Required Skills & Abilities
Minimum 5 years of hands-on systems engineering experience across Linux, server hardware, firmware, PCIe, and GPU or high-performance computing platforms.
Extensive Linux experience, particularly using Linux as an environment for hardware debugging, system-level troubleshooting, and platform investigation.
Knowledge of the Linux kernel and experience with kernel-level debugging or troubleshooting.
Strong knowledge of modern server architecture, particularly in high-performance, GPU-based environments.
Strong knowledge of NVIDIA GPU platforms and diagnostic tooling, including nvidia-smi, XID and SXID analysis, GSP and driver behaviour, NVLink, NVSwitch, Fabric Manager, DCGM diagnostics, and NCCL testing
Deep knowledge of PCIe, including topology, enumeration, root complexes, endpoints, switches, bridges, retimers, link speed and width, AER and DPC errors, completion timeouts, and link failures. Candidates should understand how protocol-level errors can relate to physical-layer or signal-integrity problems.
Experience benchmarking systems for performance, stability, power efficiency, thermal behaviour, and workload characteristics
In depth understanding of firmware interactions across BIOS/UEFI, BMC, CPLD/FPGA, GPU firmware, NIC firmware, and other platform components.
Experience with low-level hardware communication and debugging using I²C, SMBus, PMBus, register maps, bit masks, byte- and word-level data, and device datasheets.
Demonstrated ability to troubleshoot complex hardware, software, and networking issues.
Experience with deep problem investigation, root cause analysis, and performance optimization in cloud or high-performance computing environments.
Strong analytical and problem-solving skills with a performance-first mindset.
Scripting and automation using various languages (Python\Go)
Qualifications
Experience:
5 years experience
